{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Japanese Journal of Political Science\RR1\Clean\RR2\Replication\Nepal Court and Maoist Conflict Onset.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}13 Nov 2025, 11:20:07

{com}. do "C:\Users\mjoshi2\AppData\Local\Temp\STD8fe8_000000.tmp"
{txt}
{com}. set seed 123456
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mjoshi2\AppData\Local\Temp\STD8fe8_000000.tmp"
{txt}
{com}. stset time if year>1990 & year<2006, id(sn) failure(year_25death)
{err}variable {bf}time{sf} not found
{txt}{search r(111), local:r(111);}

end of do-file

{search r(111), local:r(111);}

{com}. stset if year>1990 & year<2006, id(sn) failure(year_25death)
{err}varlist required
{txt}{search r(100), local:r(100);}

{com}. clear

. use "C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Paper 1 Data & Do Files\Nepal court and conflict onset.dta" 

. sum time

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}time {c |}{res}      1,200         8.5    4.611694          1         16

{com}. keep sno sn district year dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 hilli_region mountain_region  region_east region_mid region_west region_farwest time

. save "C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Japanese Journal of Political Science\RR1\Clean\RR2\Replication\Nepal Court and Maoist Conflict Onset Replication Data.dta", replace
{txt}{p 0 4 2}
file {bf}
C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Japanese Journal of Political Science\RR1\Clean\RR2\Replication\Nepal Court and Maoist Conflict Onset Replication Data.dta{rm}
saved
{p_end}

{com}. do "C:\Users\mjoshi2\AppData\Local\Temp\STD8fe8_000000.tmp"
{txt}
{com}. set seed 123456
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mjoshi2\AppData\Local\Temp\STD8fe8_000000.tmp"
{txt}
{com}. stset time if year>1990 & year<2006, id(sn) failure(year_25death)
{err}variable {bf}year_25death{sf} not found
{txt}{search r(111), local:r(111);}

end of do-file

{search r(111), local:r(111);}

{com}. clear

. use "C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Paper 1 Data & Do Files\Nepal court and conflict onset.dta" 

. keep sno sn district year dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 hilli_region mountain_region  region_east region_mid region_west region_farwest time year_25death

. save "C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Japanese Journal of Political Science\RR1\Clean\RR2\Replication\Nepal Court and Maoist Conflict Onset Replication Data.dta", replace
{txt}{p 0 4 2}
file {bf}
C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Japanese Journal of Political Science\RR1\Clean\RR2\Replication\Nepal Court and Maoist Conflict Onset Replication Data.dta{rm}
saved
{p_end}

{com}. do "C:\Users\mjoshi2\AppData\Local\Temp\STD8fe8_000000.tmp"
{txt}
{com}. set seed 123456
{txt}
{com}. 
{txt}end of do-file

{com}. do "C:\Users\mjoshi2\AppData\Local\Temp\STD8fe8_000000.tmp"
{txt}
{com}. 
. stset time if year>1990 & year<2006, id(sn) failure(year_25death)

{txt}Survival-time data settings

{col 12}ID variable: {res}sn
{col 10}{txt}Failure event: {res}year_25death!=0 & year_25death<.
{col 1}{txt}Observed time interval: {res}(time[_n-1], time]
{col 6}{txt}Exit on or before: {res}failure
{col 7}{txt}Keep observations 
{col 17}{help j_st_ifvsoptif:{bf:if} {it:exp}}: {res}year>1990 & year<2006

{txt}{hline 74}
{res}      2,352{txt}  total observations
{res}      1,227{txt}  ignored at outset because of {bf:if} {it:exp}
{res}        249{txt}  observations begin on or after (first) failure
{hline 74}
{res}        876{txt}  observations remaining, representing
{res}         75{txt}  subjects
{res}         71{txt}  failures in single-failure-per-subject data
{res}        876{txt}  total analysis time at risk and under observation
                                                At risk from t = {res}        0
                                     {txt}Earliest observed entry t = {res}        0
                                          {txt}Last observed exit t = {res}       15
{txt}
{com}. //Kaplan-Meier graph
. sts

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn
{txt}
{com}. 
. sort sno year
{txt}
{com}. //Model 1
. streg dist_nat_gap_civil dist_nat_gap_criminal, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 29.718555}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 30.193322}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 30.196194}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 30.196195}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:2})} = {res}{ralign 6:16.43}
{txt}Log pseudolikelihood = {res}30.196195{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0003}

{txt}{ralign 87:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                   _t{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}dist_nat_gap_civil {c |}{col 23}{res}{space 2} .0112014{col 35}{space 2} .0032568{col 46}{space 1}    3.44{col 55}{space 3}0.001{col 63}{space 4} .0048182{col 76}{space 3} .0175846
{txt}dist_nat_gap_criminal {c |}{col 23}{res}{space 2}-.0031898{col 35}{space 2} .0010053{col 46}{space 1}   -3.17{col 55}{space 3}0.002{col 63}{space 4}-.0051601{col 76}{space 3}-.0012195
{txt}{space 16}_cons {c |}{col 23}{res}{space 2}-19.49749{col 35}{space 2} 2.614587{col 46}{space 1}   -7.46{col 55}{space 3}0.000{col 63}{space 4}-24.62199{col 76}{space 3}-14.37299
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/ln_p {c |}{col 23}{res}{space 2} 2.039105{col 35}{space 2} .1353131{col 46}{space 1}   15.07{col 55}{space 3}0.000{col 63}{space 4} 1.773896{col 76}{space 3} 2.304314
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                    p {c |}{col 23}{res}{space 2}  7.68373{col 35}{space 2} 1.039709{col 63}{space 4} 5.893773{col 76}{space 3}  10.0173
{txt}                  1/p {c |}{col 23}{res}{space 2} .1301451{col 35}{space 2} .0176103{col 63}{space 4} .0998273{col 76}{space 3} .1696706
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. generate sample = e(sample) 
{txt}
{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_t]dist_nat_gap_criminal = 0{p_end}

           {txt}chi2(  2) ={res}   16.43
         {txt}Prob > chi2 ={res}    0.0003

{txt}
{com}. 
. test dist_nat_gap_civil =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   11.83
{txt}{col 10}Prob > chi2 =  {res}  0.0006
{txt}
{com}. test dist_nat_gap_criminal =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_criminal = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   10.07
{txt}{col 10}Prob > chi2 =  {res}  0.0015
{txt}
{com}. 
. //Model 2
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 32.261938}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 33.339433}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 33.353625}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 33.353668}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 33.353668}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:6})} = {res}{ralign 6:28.50}
{txt}Log pseudolikelihood = {res}33.353668{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0001}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0107327{col 40}{space 2} .0025527{col 51}{space 1}    4.20{col 60}{space 3}0.000{col 68}{space 4} .0057295{col 81}{space 3} .0157358
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0024053{col 40}{space 2}  .001011{col 51}{space 1}   -2.38{col 60}{space 3}0.017{col 68}{space 4}-.0043867{col 81}{space 3}-.0004239
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0003046{col 40}{space 2} .0144632{col 51}{space 1}   -0.02{col 60}{space 3}0.983{col 68}{space 4}-.0286519{col 81}{space 3} .0280427
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.6632097{col 40}{space 2} .7141645{col 51}{space 1}   -0.93{col 60}{space 3}0.353{col 68}{space 4}-2.062946{col 81}{space 3} .7365271
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}  -.01466{col 40}{space 2} .0254319{col 51}{space 1}   -0.58{col 60}{space 3}0.564{col 68}{space 4}-.0645057{col 81}{space 3} .0351857
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0150637{col 40}{space 2} .0143865{col 51}{space 1}    1.05{col 60}{space 3}0.295{col 68}{space 4}-.0131333{col 81}{space 3} .0432607
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-20.26894{col 40}{space 2}   2.8524{col 51}{space 1}   -7.11{col 60}{space 3}0.000{col 68}{space 4}-25.85954{col 81}{space 3}-14.67834
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.079459{col 40}{space 2} .1412108{col 51}{space 1}   14.73{col 60}{space 3}0.000{col 68}{space 4} 1.802691{col 81}{space 3} 2.356227
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 8.000141{col 40}{space 2} 1.129706{col 68}{space 4}  6.06595{col 81}{space 3} 10.55107
{txt}                       1/p {c |}{col 28}{res}{space 2} .1249978{col 40}{space 2}  .017651{col 68}{space 4} .0947771{col 81}{space 3} .1648546
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_t]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_t]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_t]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_t]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_t]percent_votes1991_1999_GAP = 0{p_end}

           {txt}chi2(  6) ={res}   28.50
         {txt}Prob > chi2 ={res}    0.0001

{txt}
{com}. 
. test dist_nat_gap_civil =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   17.68
{txt}{col 10}Prob > chi2 =  {res}  0.0000
{txt}
{com}. test dist_nat_gap_criminal =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_criminal = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    5.66
{txt}{col 10}Prob > chi2 =  {res}  0.0173
{txt}
{com}. 
. //Model 3
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 39.514244}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 45.345468}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 45.516971}  
Iteration 4:{space 2}Log pseudolikelihood = {res:  45.52319}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 45.523201}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 45.523201}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:9})} = {res}{ralign 6:62.04}
{txt}Log pseudolikelihood = {res}45.523201{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0151849{col 40}{space 2} .0034499{col 51}{space 1}    4.40{col 60}{space 3}0.000{col 68}{space 4} .0084233{col 81}{space 3} .0219466
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0054029{col 40}{space 2} .0013264{col 51}{space 1}   -4.07{col 60}{space 3}0.000{col 68}{space 4}-.0080026{col 81}{space 3}-.0028033
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .000358{col 40}{space 2} .0129803{col 51}{space 1}    0.03{col 60}{space 3}0.978{col 68}{space 4} -.025083{col 81}{space 3} .0257989
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-2.147982{col 40}{space 2} 1.433719{col 51}{space 1}   -1.50{col 60}{space 3}0.134{col 68}{space 4} -4.95802{col 81}{space 3} .6620561
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0393576{col 40}{space 2} .0242909{col 51}{space 1}   -1.62{col 60}{space 3}0.105{col 68}{space 4}-.0869669{col 81}{space 3} .0082517
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0030316{col 40}{space 2} .0141817{col 51}{space 1}    0.21{col 60}{space 3}0.831{col 68}{space 4}-.0247641{col 81}{space 3} .0308273
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}-2.958295{col 40}{space 2} 1.558501{col 51}{space 1}   -1.90{col 60}{space 3}0.058{col 68}{space 4}-6.012902{col 81}{space 3} .0963115
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .9568317{col 40}{space 2} .2881563{col 51}{space 1}    3.32{col 60}{space 3}0.001{col 68}{space 4} .3920557{col 81}{space 3} 1.521608
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.0204221{col 40}{space 2} .1479636{col 51}{space 1}   -0.14{col 60}{space 3}0.890{col 68}{space 4}-.3104255{col 81}{space 3} .2695812
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-33.40984{col 40}{space 2} 4.722408{col 51}{space 1}   -7.07{col 60}{space 3}0.000{col 68}{space 4}-42.66559{col 81}{space 3}-24.15409
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.250366{col 40}{space 2} .1533091{col 51}{space 1}   14.68{col 60}{space 3}0.000{col 68}{space 4} 1.949885{col 81}{space 3} 2.550846
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 9.491205{col 40}{space 2} 1.455088{col 68}{space 4} 7.027881{col 81}{space 3} 12.81794
{txt}                       1/p {c |}{col 28}{res}{space 2} .1053607{col 40}{space 2} .0161528{col 68}{space 4} .0780157{col 81}{space 3} .1422904
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_t]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_t]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_t]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_t]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_t]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_t]cast_eth_fract = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_t]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_t]ln_abs_total2001 = 0{p_end}

           {txt}chi2(  9) ={res}   62.04
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. 
. test dist_nat_gap_civil =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   19.37
{txt}{col 10}Prob > chi2 =  {res}  0.0000
{txt}
{com}. test dist_nat_gap_criminal =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_criminal = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   16.59
{txt}{col 10}Prob > chi2 =  {res}  0.0000
{txt}
{com}. 
. //Model 4
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 35.262999}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 49.237285}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 49.629864}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 49.641796}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 49.641817}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 49.641817}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:10})} = {res}{ralign 6:78.52}
{txt}Log pseudolikelihood = {res}49.641817{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0114975{col 40}{space 2} .0037362{col 51}{space 1}    3.08{col 60}{space 3}0.002{col 68}{space 4} .0041746{col 81}{space 3} .0188203
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0052596{col 40}{space 2}  .001369{col 51}{space 1}   -3.84{col 60}{space 3}0.000{col 68}{space 4}-.0079427{col 81}{space 3}-.0025765
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0051588{col 40}{space 2} .0134033{col 51}{space 1}   -0.38{col 60}{space 3}0.700{col 68}{space 4}-.0314288{col 81}{space 3} .0211113
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.710859{col 40}{space 2} 1.160581{col 51}{space 1}   -1.47{col 60}{space 3}0.140{col 68}{space 4}-3.985556{col 81}{space 3} .5638378
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0743925{col 40}{space 2} .0218007{col 51}{space 1}   -3.41{col 60}{space 3}0.001{col 68}{space 4}-.1171212{col 81}{space 3}-.0316639
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0074126{col 40}{space 2} .0131364{col 51}{space 1}    0.56{col 60}{space 3}0.573{col 68}{space 4}-.0183342{col 81}{space 3} .0331594
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .9715891{col 40}{space 2} .2782253{col 51}{space 1}    3.49{col 60}{space 3}0.000{col 68}{space 4} .4262776{col 81}{space 3} 1.516901
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.0787981{col 40}{space 2} .1476569{col 51}{space 1}   -0.53{col 60}{space 3}0.594{col 68}{space 4}-.3682004{col 81}{space 3} .2106041
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.166522{col 40}{space 2} .3383473{col 51}{space 1}    3.45{col 60}{space 3}0.001{col 68}{space 4} .5033737{col 81}{space 3} 1.829671
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} .7031905{col 40}{space 2} .4976249{col 51}{space 1}    1.41{col 60}{space 3}0.158{col 68}{space 4}-.2721363{col 81}{space 3} 1.678517
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-37.58896{col 40}{space 2} 5.658993{col 51}{space 1}   -6.64{col 60}{space 3}0.000{col 68}{space 4}-48.68038{col 81}{space 3}-26.49754
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.310941{col 40}{space 2} .1517856{col 51}{space 1}   15.23{col 60}{space 3}0.000{col 68}{space 4} 2.013446{col 81}{space 3} 2.608435
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 10.08391{col 40}{space 2} 1.530592{col 68}{space 4} 7.489083{col 81}{space 3} 13.57779
{txt}                       1/p {c |}{col 28}{res}{space 2} .0991679{col 40}{space 2} .0150523{col 68}{space 4} .0736497{col 81}{space 3} .1335277
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_t]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_t]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_t]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_t]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_t]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_t]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_t]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_t]hilli_region = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_t]mountain_region = 0{p_end}

           {txt}chi2( 10) ={res}   78.52
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. test dist_nat_gap_civil =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    9.47
{txt}{col 10}Prob > chi2 =  {res}  0.0021
{txt}
{com}. test dist_nat_gap_criminal =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_criminal = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   14.76
{txt}{col 10}Prob > chi2 =  {res}  0.0001
{txt}
{com}. 
. //Model 5
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res:  28.18993}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 49.084106}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 49.758278}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 49.764987}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 49.764991}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:12})} = {res}{ralign 6:89.80}
{txt}Log pseudolikelihood = {res}49.764991{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}  .013924{col 40}{space 2} .0038944{col 51}{space 1}    3.58{col 60}{space 3}0.000{col 68}{space 4} .0062912{col 81}{space 3} .0215568
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} -.004383{col 40}{space 2} .0012169{col 51}{space 1}   -3.60{col 60}{space 3}0.000{col 68}{space 4}-.0067681{col 81}{space 3}-.0019978
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}   .01195{col 40}{space 2} .0128584{col 51}{space 1}    0.93{col 60}{space 3}0.353{col 68}{space 4}-.0132521{col 81}{space 3}  .037152
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} -2.05365{col 40}{space 2} 1.736939{col 51}{space 1}   -1.18{col 60}{space 3}0.237{col 68}{space 4}-5.457988{col 81}{space 3} 1.350689
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} -.029981{col 40}{space 2} .0269348{col 51}{space 1}   -1.11{col 60}{space 3}0.266{col 68}{space 4}-.0827722{col 81}{space 3} .0228102
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2}-.0066413{col 40}{space 2} .0155077{col 51}{space 1}   -0.43{col 60}{space 3}0.668{col 68}{space 4}-.0370358{col 81}{space 3} .0237532
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .6835745{col 40}{space 2} .3205634{col 51}{space 1}    2.13{col 60}{space 3}0.033{col 68}{space 4} .0552818{col 81}{space 3} 1.311867
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0644446{col 40}{space 2} .1846551{col 51}{space 1}    0.35{col 60}{space 3}0.727{col 68}{space 4}-.2974727{col 81}{space 3} .4263619
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-1.283697{col 40}{space 2} .3519322{col 51}{space 1}   -3.65{col 60}{space 3}0.000{col 68}{space 4}-1.973471{col 81}{space 3}-.5939222
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-1.123389{col 40}{space 2} .4012162{col 51}{space 1}   -2.80{col 60}{space 3}0.005{col 68}{space 4}-1.909758{col 81}{space 3}-.3370199
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-1.491564{col 40}{space 2} .4224862{col 51}{space 1}   -3.53{col 60}{space 3}0.000{col 68}{space 4}-2.319622{col 81}{space 3}-.6635065
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.8643724{col 40}{space 2} .4200344{col 51}{space 1}   -2.06{col 60}{space 3}0.040{col 68}{space 4}-1.687625{col 81}{space 3}-.0411201
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-33.34314{col 40}{space 2} 4.908895{col 51}{space 1}   -6.79{col 60}{space 3}0.000{col 68}{space 4} -42.9644{col 81}{space 3}-23.72189
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.302809{col 40}{space 2} .1515258{col 51}{space 1}   15.20{col 60}{space 3}0.000{col 68}{space 4} 2.005824{col 81}{space 3} 2.599794
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 10.00224{col 40}{space 2} 1.515598{col 68}{space 4} 7.432217{col 81}{space 3} 13.46097
{txt}                       1/p {c |}{col 28}{res}{space 2} .0999776{col 40}{space 2} .0151492{col 68}{space 4} .0742889{col 81}{space 3} .1345494
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_t]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_t]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_t]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_t]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_t]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_t]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_t]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_t]region_east = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_t]region_mid = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} [_t]region_west = 0{p_end}
{p 0 7}{space 1}{text:(12)}{space 1} [_t]region_farwest = 0{p_end}

           {txt}chi2( 12) ={res}   89.80
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. test dist_nat_gap_civil =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   12.78
{txt}{col 10}Prob > chi2 =  {res}  0.0003
{txt}
{com}. test dist_nat_gap_criminal =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_criminal = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   12.97
{txt}{col 10}Prob > chi2 =  {res}  0.0003
{txt}
{com}. 
. //Model 6
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 45.318014}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 54.014188}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 55.102958}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 55.131957}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 55.132307}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 55.132307}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:15})} = {res}{ralign 6:86.44}
{txt}Log pseudolikelihood = {res}55.132307{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0109657{col 40}{space 2} .0039142{col 51}{space 1}    2.80{col 60}{space 3}0.005{col 68}{space 4}  .003294{col 81}{space 3} .0186374
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0047537{col 40}{space 2} .0013775{col 51}{space 1}   -3.45{col 60}{space 3}0.001{col 68}{space 4}-.0074535{col 81}{space 3}-.0020538
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0004181{col 40}{space 2} .0139724{col 51}{space 1}   -0.03{col 60}{space 3}0.976{col 68}{space 4}-.0278036{col 81}{space 3} .0269673
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.989202{col 40}{space 2} 1.148411{col 51}{space 1}   -1.73{col 60}{space 3}0.083{col 68}{space 4}-4.240046{col 81}{space 3} .2616428
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0390471{col 40}{space 2} .0268074{col 51}{space 1}   -1.46{col 60}{space 3}0.145{col 68}{space 4}-.0915887{col 81}{space 3} .0134944
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2}-.0036289{col 40}{space 2} .0148244{col 51}{space 1}   -0.24{col 60}{space 3}0.807{col 68}{space 4}-.0326843{col 81}{space 3} .0254264
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.448253{col 40}{space 2} .3711774{col 51}{space 1}    3.90{col 60}{space 3}0.000{col 68}{space 4} .7207585{col 81}{space 3} 2.175747
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} -.203216{col 40}{space 2} .1891792{col 51}{space 1}   -1.07{col 60}{space 3}0.283{col 68}{space 4}-.5740005{col 81}{space 3} .1675684
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}-2.155467{col 40}{space 2} 1.921156{col 51}{space 1}   -1.12{col 60}{space 3}0.262{col 68}{space 4}-5.920863{col 81}{space 3} 1.609929
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-1.238967{col 40}{space 2} .3253576{col 51}{space 1}   -3.81{col 60}{space 3}0.000{col 68}{space 4}-1.876656{col 81}{space 3}-.6012777
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-1.441462{col 40}{space 2}  .437548{col 51}{space 1}   -3.29{col 60}{space 3}0.001{col 68}{space 4} -2.29904{col 81}{space 3}-.5838834
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-1.184886{col 40}{space 2} .3996664{col 51}{space 1}   -2.96{col 60}{space 3}0.003{col 68}{space 4}-1.968217{col 81}{space 3}-.4015538
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-1.040852{col 40}{space 2} .4497347{col 51}{space 1}   -2.31{col 60}{space 3}0.021{col 68}{space 4}-1.922316{col 81}{space 3}-.1593883
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.166189{col 40}{space 2} .3831684{col 51}{space 1}    3.04{col 60}{space 3}0.002{col 68}{space 4} .4151924{col 81}{space 3} 1.917185
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} .8665506{col 40}{space 2} .5889057{col 51}{space 1}    1.47{col 60}{space 3}0.141{col 68}{space 4}-.2876834{col 81}{space 3} 2.020785
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-41.71279{col 40}{space 2} 6.213698{col 51}{space 1}   -6.71{col 60}{space 3}0.000{col 68}{space 4}-53.89141{col 81}{space 3}-29.53416
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.388315{col 40}{space 2} .1464975{col 51}{space 1}   16.30{col 60}{space 3}0.000{col 68}{space 4} 2.101186{col 81}{space 3} 2.675445
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 10.89513{col 40}{space 2} 1.596109{col 68}{space 4} 8.175857{col 81}{space 3} 14.51881
{txt}                       1/p {c |}{col 28}{res}{space 2} .0917842{col 40}{space 2} .0134462{col 68}{space 4} .0688761{col 81}{space 3} .1223113
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_t]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_t]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_t]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_t]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_t]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_t]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_t]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_t]cast_eth_fract = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_t]region_east = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} [_t]region_mid = 0{p_end}
{p 0 7}{space 1}{text:(12)}{space 1} [_t]region_west = 0{p_end}
{p 0 7}{space 1}{text:(13)}{space 1} [_t]region_farwest = 0{p_end}
{p 0 7}{space 1}{text:(14)}{space 1} [_t]hilli_region = 0{p_end}
{p 0 7}{space 1}{text:(15)}{space 1} [_t]mountain_region = 0{p_end}

           {txt}chi2( 15) ={res}   86.44
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. test dist_nat_gap_civil =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_civil = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    7.85
{txt}{col 10}Prob > chi2 =  {res}  0.0051
{txt}
{com}. test dist_nat_gap_criminal =0

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_t]dist_nat_gap_criminal = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   11.91
{txt}{col 10}Prob > chi2 =  {res}  0.0006
{txt}
{com}. 
. //sum dist_nat_gap_civil dist_nat_gap_criminal if sample==1
. 
. //display -6.350737 -87.62705
. //-93.977787
. //display -6.350737+87.62705
. //81.276313
. //One standard deviation below and above mean
. 
. stcurve, survival at1(dist_nat_gap_civil=-93.977787)at2(dist_nat_gap_civil=81.276313)
{txt}{p 0 6 2}note: function evaluated at specified values of selected covariates and overall means of other covariates (if any).{p_end}
{res}{txt}
{com}. 
. //display -2.72684 -40.40115
. //-43.12799
. 
. //display -2.72684 + 40.40115
. //37.67431
. 
. stcurve, survival at1(dist_nat_gap_criminal=-43.12799) at2(dist_nat_gap_criminal=37.67431)
{txt}{p 0 6 2}note: function evaluated at specified values of selected covariates and overall means of other covariates (if any).{p_end}
{res}{txt}
{com}. 
. pwcorr dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  region_east region_mid region_west region_farwest _d if sample ==1

             {txt}{c |} dist_~il dist_~al litrat~P road_d~P lifeex~P percen~P cast_e~t
{hline 13}{c +}{hline 63}
dist_nat_~il {c |} {res}  1.0000 
{txt}dist_nat_~al {c |} {res}  0.1480   1.0000 
{txt}litrate_19~P {c |} {res}  0.0347   0.0031   1.0000 
{txt}road_densi~P {c |} {res}  0.0250  -0.0004   0.4722   1.0000 
{txt}lifeexp_19~P {c |} {res}  0.0110   0.0301   0.5065   0.4118   1.0000 
{txt}percent_vo~P {c |} {res} -0.0385  -0.0073  -0.0841   0.1547   0.1395   1.0000 
{txt}cast_eth_f~t {c |} {res}  0.0108   0.0233   0.0569   0.0171   0.5262   0.2639   1.0000 
      {txt}ln_pop {c |} {res}  0.0549   0.0618   0.1873   0.3867   0.4734   0.1779   0.6527 
{txt}ln_abs_~2001 {c |} {res}  0.0886   0.0747   0.3836   0.1184   0.3192  -0.1878   0.3705 
{txt}hilli_region {c |} {res}  0.0565   0.0254   0.3152   0.1013   0.1234  -0.3221  -0.1109 
{txt}mountain_r~n {c |} {res} -0.1045  -0.0414  -0.1796  -0.2743  -0.3822  -0.0114  -0.4159 
 {txt}region_east {c |} {res}  0.0012   0.0108   0.2752  -0.0798   0.3321   0.1164   0.3274 
  {txt}region_mid {c |} {res} -0.0265   0.0259  -0.0748   0.4622   0.2978   0.1563   0.1297 
 {txt}region_west {c |} {res}  0.0398  -0.0091   0.3186  -0.1426   0.0969  -0.1576  -0.0147 
{txt}region_far~t {c |} {res}  0.0240   0.0168  -0.1935  -0.1336  -0.4321  -0.3021  -0.4062 
          {txt}_d {c |} {res}  0.0801  -0.0253  -0.0199  -0.0259  -0.0240   0.0062   0.0163 

             {txt}{c |}   ln_pop ln_~2001 hilli_~n mounta~n regi~ast region~d re~_west
{hline 13}{c +}{hline 63}
      ln_pop {c |} {res}  1.0000 
{txt}ln_abs_~2001 {c |} {res}  0.6810   1.0000 
{txt}hilli_region {c |} {res}  0.0500   0.2583   1.0000 
{txt}mountain_r~n {c |} {res} -0.6571  -0.4990  -0.4803   1.0000 
 {txt}region_east {c |} {res}  0.1164   0.0477  -0.0120  -0.0022   1.0000 
  {txt}region_mid {c |} {res}  0.2574  -0.1612  -0.0709  -0.1967  -0.3205   1.0000 
 {txt}region_west {c |} {res} -0.1335   0.3001   0.1521  -0.0378  -0.2901  -0.3205   1.0000 
{txt}region_far~t {c |} {res} -0.0590   0.1626  -0.0490   0.1528  -0.1966  -0.2172  -0.1966 
          {txt}_d {c |} {res}  0.0674   0.0218   0.0212  -0.0188   0.0003  -0.0149  -0.0197 

             {txt}{c |} re~rwest       _d
{hline 13}{c +}{hline 18}
region_far~t {c |} {res}  1.0000 
          {txt}_d {c |} {res}  0.0085   1.0000 
{txt}
{com}. 
. sum dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  region_east region_mid region_west region_farwest _d if sample ==1

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
dist_nat_~il {c |}{res}        876   -6.326296    87.67412  -1659.567   123.7096
{txt}dist_nat_~al {c |}{res}        876   -2.739625    40.42245  -496.9529   128.6676
{txt}litrate_19~P {c |}{res}        876    .4655335    11.29072  -25.01067   31.98667
{txt}road_densi~P {c |}{res}        876    .0114313    .3204351  -.1899205    1.86788
{txt}lifeexp_19~P {c |}{res}        876    .3013079    6.739406  -22.17333   14.82667
{txt}{hline 13}{c +}{hline 57}
percent_vo~P {c |}{res}        876    .1382067    9.647047  -64.42893   22.49114
{txt}cast_eth_f~t {c |}{res}        876    .7959034    .1042198   .5427595   .9419107
{txt}{space 6}ln_pop {c |}{res}        876    12.27733    .9151427   8.587278   13.83956
{txt}ln_abs_~2001 {c |}{res}        876    8.615499    1.354923   4.912655   10.71103
{txt}hilli_region {c |}{res}        876    .5136986    .5000978          0          1
{txt}{hline 13}{c +}{hline 57}
mountain_r~n {c |}{res}        876    .1792237    .3837587          0          1
{txt}{space 1}region_east {c |}{res}        876    .2248858    .4177456          0          1
{txt}{space 2}region_mid {c |}{res}        876    .2614155    .4396568          0          1
{txt}{space 1}region_west {c |}{res}        876    .2248858    .4177456          0          1
{txt}region_far~t {c |}{res}        876    .1175799     .322294          0          1
{txt}{hline 13}{c +}{hline 57}
{space 10}_d {c |}{res}        876    .0810502    .2730681          0          1
{txt}
{com}. 
. graph matrix dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  region_east region_mid region_west region_farwest _d  if sample ==1, half  
{res}{txt}
{com}. 
. collin _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  region_east region_mid region_west region_farwest if sample ==1
{txt}(obs=876)

  Collinearity Diagnostics

                        SQRT                   R-
  Variable      VIF     VIF    Tolerance    Squared
----------------------------------------------------
        {res}_d      1.03    1.02    0.9689      0.0311
dist_nat_gap_civil      1.05    1.02    0.9532      0.0468
dist_nat_gap_criminal      1.03    1.02    0.9667      0.0333
litrate_1991_2001_GAP      3.12    1.77    0.3206      0.6794
road_density_GAP      2.87    1.69    0.3488      0.6512
lifeexp_1990_2011_GAP      2.90    1.70    0.3449      0.6551
percent_votes1991_1999_GAP      1.46    1.21    0.6827      0.3173
cast_eth_fract      3.55    1.88    0.2817      0.7183
    ln_pop      7.80    2.79    0.1282      0.8718
ln_abs_total2001      5.03    2.24    0.1990      0.8010
hilli_region      2.10    1.45    0.4762      0.5238
mountain_region      3.01    1.74    0.3319      0.6681
region_east      3.36    1.83    0.2973      0.7027
region_mid      2.94    1.71    0.3403      0.6597
region_west      3.46    1.86    0.2889      0.7111
region_farwest      2.30    1.52    0.4342      0.5658
{txt}----------------------------------------------------
  Mean VIF{res}      2.94

{txt}                           Cond
        Eigenval          Index
---------------------------------
{res}    1     5.6825          1.0000
    2     2.4234          1.5313
    3     1.4748          1.9629
    4     1.2544          2.1284
    5     1.1330          2.2395
    6     0.9628          2.4294
    7     0.9447          2.4526
    8     0.8080          2.6520
    9     0.7875          2.6862
    10     0.6084          3.0562
    11     0.4217          3.6708
    12     0.2287          4.9848
    13     0.1820          5.5884
    14     0.0783          8.5181
    15     0.0059         30.9324
    16     0.0036         39.6132
    17     0.0005        108.3911
{txt}---------------------------------
 Condition Number{res}       108.3911 
{txt} Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept)
 Det(correlation matrix){res}    0.0005
{txt}
{com}. 
. 
. 
. //Alternative Model Specificaiton _d as dependent variable
. 
. 
. //Model 4 Logit
. xtlogit _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  hilli_region mountain_region  if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-232.11701}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-217.25997}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-216.67312}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-216.67225}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-216.67225}  
{res}
{txt}Fitting full model:

tau = {res} 0.0    {txt}Log pseudolikelihood = {res}-216.67225
{txt}tau = {res} 0.1    {txt}Log pseudolikelihood = {res}-218.94346

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-218.94346}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-216.69182}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-216.67655}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-216.67323}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-216.67248}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-216.67229}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-216.67228}  
{res}
{txt}Calculating robust standard errors ...

{col 1}Random-effects logistic regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:10})}{col 70} = {res}{ralign 6:51.18}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-216.67228}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0312562{col 40}{space 2} .0067559{col 51}{space 1}    4.63{col 60}{space 3}0.000{col 68}{space 4} .0180148{col 81}{space 3} .0444976
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0056952{col 40}{space 2} .0024283{col 51}{space 1}   -2.35{col 60}{space 3}0.019{col 68}{space 4}-.0104546{col 81}{space 3}-.0009358
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0054409{col 40}{space 2} .0131852{col 51}{space 1}    0.41{col 60}{space 3}0.680{col 68}{space 4}-.0204016{col 81}{space 3} .0312834
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.357472{col 40}{space 2} .6468391{col 51}{space 1}   -2.10{col 60}{space 3}0.036{col 68}{space 4}-2.625253{col 81}{space 3}-.0896905
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0473376{col 40}{space 2}  .018744{col 51}{space 1}   -2.53{col 60}{space 3}0.012{col 68}{space 4}-.0840751{col 81}{space 3}-.0106001
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0292866{col 40}{space 2} .0171376{col 51}{space 1}    1.71{col 60}{space 3}0.087{col 68}{space 4}-.0043024{col 81}{space 3} .0628757
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.769969{col 40}{space 2} .4161428{col 51}{space 1}    4.25{col 60}{space 3}0.000{col 68}{space 4} .9543446{col 81}{space 3} 2.585594
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.2544207{col 40}{space 2} .1060617{col 51}{space 1}   -2.40{col 60}{space 3}0.016{col 68}{space 4}-.4622977{col 81}{space 3}-.0465437
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.122377{col 40}{space 2} .3883542{col 51}{space 1}    2.89{col 60}{space 3}0.004{col 68}{space 4} .3612172{col 81}{space 3} 1.883538
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.477029{col 40}{space 2} .6009737{col 51}{space 1}    2.46{col 60}{space 3}0.014{col 68}{space 4}  .299142{col 81}{space 3} 2.654916
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-23.29081{col 40}{space 2} 5.118228{col 51}{space 1}   -4.55{col 60}{space 3}0.000{col 68}{space 4}-33.32236{col 81}{space 3}-13.25927
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2} -13.6032{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2}  .001112{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 3.76e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_d]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_d]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_d]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_d]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_d]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_d]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_d]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_d]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_d]hilli_region = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_d]mountain_region = 0{p_end}

           {txt}chi2( 10) ={res}   51.18
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. 
.  //Model 5 Logit
.  xtlogit _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-234.56529}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-219.98581}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-219.18675}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-219.18555}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-219.18555}  
{res}
{txt}Fitting full model:

tau = {res} 0.0    {txt}Log pseudolikelihood = {res}-219.18555
{txt}tau = {res} 0.1    {txt}Log pseudolikelihood = {res}-221.66937

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-221.66937}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-219.20125}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-219.18563}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-219.18556}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-219.18556}  
{res}
{txt}Calculating robust standard errors ...

{col 1}Random-effects logistic regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:12})}{col 70} = {res}{ralign 6:65.67}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-219.18556}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0322086{col 40}{space 2} .0067653{col 51}{space 1}    4.76{col 60}{space 3}0.000{col 68}{space 4}  .018949{col 81}{space 3} .0454683
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0049939{col 40}{space 2} .0023077{col 51}{space 1}   -2.16{col 60}{space 3}0.030{col 68}{space 4}-.0095169{col 81}{space 3}-.0004709
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0218142{col 40}{space 2} .0130995{col 51}{space 1}    1.67{col 60}{space 3}0.096{col 68}{space 4}-.0038603{col 81}{space 3} .0474886
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.422587{col 40}{space 2} .8989174{col 51}{space 1}   -1.58{col 60}{space 3}0.114{col 68}{space 4}-3.184432{col 81}{space 3} .3392592
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0259773{col 40}{space 2} .0227166{col 51}{space 1}   -1.14{col 60}{space 3}0.253{col 68}{space 4} -.070501{col 81}{space 3} .0185465
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0058319{col 40}{space 2} .0132647{col 51}{space 1}    0.44{col 60}{space 3}0.660{col 68}{space 4}-.0201665{col 81}{space 3} .0318302
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.268322{col 40}{space 2} .2053442{col 51}{space 1}    6.18{col 60}{space 3}0.000{col 68}{space 4} .8658545{col 81}{space 3} 1.670789
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.3440312{col 40}{space 2} .0961886{col 51}{space 1}   -3.58{col 60}{space 3}0.000{col 68}{space 4}-.5325574{col 81}{space 3} -.155505
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.5009359{col 40}{space 2} .2667704{col 51}{space 1}   -1.88{col 60}{space 3}0.060{col 68}{space 4}-1.023796{col 81}{space 3} .0219246
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.4989169{col 40}{space 2} .2781252{col 51}{space 1}   -1.79{col 60}{space 3}0.073{col 68}{space 4}-1.044032{col 81}{space 3} .0461984
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.2171537{col 40}{space 2}  .267367{col 51}{space 1}   -0.81{col 60}{space 3}0.417{col 68}{space 4}-.7411834{col 81}{space 3} .3068759
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.0110622{col 40}{space 2} .2428077{col 51}{space 1}   -0.05{col 60}{space 3}0.964{col 68}{space 4}-.4869564{col 81}{space 3} .4648321
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-15.16544{col 40}{space 2} 2.212141{col 51}{space 1}   -6.86{col 60}{space 3}0.000{col 68}{space 4}-19.50115{col 81}{space 3}-10.82972
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2} -16.0791{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0003225{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 3.16e-08{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_d]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_d]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_d]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_d]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_d]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_d]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_d]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_d]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_d]region_east = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_d]region_mid = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} [_d]region_west = 0{p_end}
{p 0 7}{space 1}{text:(12)}{space 1} [_d]region_farwest = 0{p_end}

           {txt}chi2( 12) ={res}   65.67
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. 
. //Model 6 Logit
. xtlogit _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-231.18192}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-215.47978}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-214.55355}  
Iteration 4:{space 2}Log pseudolikelihood = {res: -214.5509}  
Iteration 5:{space 2}Log pseudolikelihood = {res: -214.5509}  
{res}
{txt}Fitting full model:

tau = {res} 0.0    {txt}Log pseudolikelihood = {res} -214.5509
{txt}tau = {res} 0.1    {txt}Log pseudolikelihood = {res}-216.78233

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-216.78233}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-214.57362}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-214.55526}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-214.55168}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-214.55108}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-214.55094}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-214.55093}  
Iteration 7:{space 2}Log pseudolikelihood = {res:-214.55092}  
{res}
{txt}Calculating robust standard errors ...

{col 1}Random-effects logistic regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:15})}{col 70} = {res}{ralign 6:62.93}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-214.55092}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0319441{col 40}{space 2} .0068762{col 51}{space 1}    4.65{col 60}{space 3}0.000{col 68}{space 4} .0184669{col 81}{space 3} .0454213
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0056994{col 40}{space 2} .0024386{col 51}{space 1}   -2.34{col 60}{space 3}0.019{col 68}{space 4}-.0104791{col 81}{space 3}-.0009197
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .002176{col 40}{space 2} .0164157{col 51}{space 1}    0.13{col 60}{space 3}0.895{col 68}{space 4}-.0299982{col 81}{space 3} .0343503
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.599863{col 40}{space 2} .8176381{col 51}{space 1}   -1.96{col 60}{space 3}0.050{col 68}{space 4}-3.202404{col 81}{space 3} .0026783
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0099819{col 40}{space 2} .0247148{col 51}{space 1}   -0.40{col 60}{space 3}0.686{col 68}{space 4} -.058422{col 81}{space 3} .0384582
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0338828{col 40}{space 2} .0190508{col 51}{space 1}    1.78{col 60}{space 3}0.075{col 68}{space 4}-.0034561{col 81}{space 3} .0712218
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}  2.23832{col 40}{space 2} .5338065{col 51}{space 1}    4.19{col 60}{space 3}0.000{col 68}{space 4} 1.192078{col 81}{space 3} 3.284561
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.3903389{col 40}{space 2} .1290858{col 51}{space 1}   -3.02{col 60}{space 3}0.002{col 68}{space 4}-.6433424{col 81}{space 3}-.1373353
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} -2.89544{col 40}{space 2}  2.35926{col 51}{space 1}   -1.23{col 60}{space 3}0.220{col 68}{space 4}-7.519505{col 81}{space 3} 1.728625
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.4714863{col 40}{space 2} .4502807{col 51}{space 1}   -1.05{col 60}{space 3}0.295{col 68}{space 4} -1.35402{col 81}{space 3} .4110476
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.7090181{col 40}{space 2}  .555086{col 51}{space 1}   -1.28{col 60}{space 3}0.201{col 68}{space 4}-1.796967{col 81}{space 3} .3789305
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.1747052{col 40}{space 2} .3757913{col 51}{space 1}   -0.46{col 60}{space 3}0.642{col 68}{space 4}-.9112426{col 81}{space 3} .5618323
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.1141763{col 40}{space 2}  .332951{col 51}{space 1}   -0.34{col 60}{space 3}0.732{col 68}{space 4}-.7667482{col 81}{space 3} .5383957
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.184415{col 40}{space 2} .5815769{col 51}{space 1}    2.04{col 60}{space 3}0.042{col 68}{space 4} .0445453{col 81}{space 3} 2.324285
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.616854{col 40}{space 2} .9178238{col 51}{space 1}    1.76{col 60}{space 3}0.078{col 68}{space 4}-.1820476{col 81}{space 3} 3.415756
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} -25.3392{col 40}{space 2} 7.269554{col 51}{space 1}   -3.49{col 60}{space 3}0.000{col 68}{space 4}-39.58727{col 81}{space 3}-11.09114
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2} -14.0844{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0008742{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 2.32e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_d]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_d]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_d]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_d]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_d]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_d]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_d]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_d]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_d]cast_eth_fract = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_d]region_east = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} [_d]region_mid = 0{p_end}
{p 0 7}{space 1}{text:(12)}{space 1} [_d]region_west = 0{p_end}
{p 0 7}{space 1}{text:(13)}{space 1} [_d]region_farwest = 0{p_end}
{p 0 7}{space 1}{text:(14)}{space 1} [_d]hilli_region = 0{p_end}
{p 0 7}{space 1}{text:(15)}{space 1} [_d]mountain_region = 0{p_end}

           {txt}chi2( 15) ={res}   62.93
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. 
. //Logit margin graph
. gen MYVAR = dist_nat_gap_civil
{txt}(102 missing values generated)

{com}. xtlogit _d MYVAR dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-231.18192}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-215.47978}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-214.55355}  
Iteration 4:{space 2}Log pseudolikelihood = {res: -214.5509}  
Iteration 5:{space 2}Log pseudolikelihood = {res: -214.5509}  
{res}
{txt}Fitting full model:

tau = {res} 0.0    {txt}Log pseudolikelihood = {res} -214.5509
{txt}tau = {res} 0.1    {txt}Log pseudolikelihood = {res}-216.78233

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-216.78233}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-214.57362}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-214.55526}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-214.55168}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-214.55108}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-214.55094}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-214.55093}  
Iteration 7:{space 2}Log pseudolikelihood = {res:-214.55092}  
{res}
{txt}Calculating robust standard errors ...

{col 1}Random-effects logistic regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:15})}{col 70} = {res}{ralign 6:62.93}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-214.55092}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}MYVAR {c |}{col 28}{res}{space 2} .0319441{col 40}{space 2} .0068762{col 51}{space 1}    4.65{col 60}{space 3}0.000{col 68}{space 4} .0184669{col 81}{space 3} .0454213
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0056994{col 40}{space 2} .0024386{col 51}{space 1}   -2.34{col 60}{space 3}0.019{col 68}{space 4}-.0104791{col 81}{space 3}-.0009197
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .002176{col 40}{space 2} .0164157{col 51}{space 1}    0.13{col 60}{space 3}0.895{col 68}{space 4}-.0299982{col 81}{space 3} .0343503
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.599863{col 40}{space 2} .8176381{col 51}{space 1}   -1.96{col 60}{space 3}0.050{col 68}{space 4}-3.202404{col 81}{space 3} .0026783
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0099819{col 40}{space 2} .0247148{col 51}{space 1}   -0.40{col 60}{space 3}0.686{col 68}{space 4} -.058422{col 81}{space 3} .0384582
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0338828{col 40}{space 2} .0190508{col 51}{space 1}    1.78{col 60}{space 3}0.075{col 68}{space 4}-.0034561{col 81}{space 3} .0712218
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}  2.23832{col 40}{space 2} .5338065{col 51}{space 1}    4.19{col 60}{space 3}0.000{col 68}{space 4} 1.192078{col 81}{space 3} 3.284561
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.3903389{col 40}{space 2} .1290858{col 51}{space 1}   -3.02{col 60}{space 3}0.002{col 68}{space 4}-.6433424{col 81}{space 3}-.1373353
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} -2.89544{col 40}{space 2}  2.35926{col 51}{space 1}   -1.23{col 60}{space 3}0.220{col 68}{space 4}-7.519505{col 81}{space 3} 1.728625
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.4714863{col 40}{space 2} .4502807{col 51}{space 1}   -1.05{col 60}{space 3}0.295{col 68}{space 4} -1.35402{col 81}{space 3} .4110476
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.7090181{col 40}{space 2}  .555086{col 51}{space 1}   -1.28{col 60}{space 3}0.201{col 68}{space 4}-1.796967{col 81}{space 3} .3789305
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.1747052{col 40}{space 2} .3757913{col 51}{space 1}   -0.46{col 60}{space 3}0.642{col 68}{space 4}-.9112426{col 81}{space 3} .5618323
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.1141763{col 40}{space 2}  .332951{col 51}{space 1}   -0.34{col 60}{space 3}0.732{col 68}{space 4}-.7667482{col 81}{space 3} .5383957
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.184415{col 40}{space 2} .5815769{col 51}{space 1}    2.04{col 60}{space 3}0.042{col 68}{space 4} .0445453{col 81}{space 3} 2.324285
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.616854{col 40}{space 2} .9178238{col 51}{space 1}    1.76{col 60}{space 3}0.078{col 68}{space 4}-.1820476{col 81}{space 3} 3.415756
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} -25.3392{col 40}{space 2} 7.269554{col 51}{space 1}   -3.49{col 60}{space 3}0.000{col 68}{space 4}-39.58727{col 81}{space 3}-11.09114
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2} -14.0844{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0008742{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 2.32e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, atmeans at(MYVAR=(-200(20)200)) saving(file1, replace)
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:876}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(_d=1), predict(pr)}{p_end}
{p2colreset}{...}
{lalign 8:1._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-200}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:2._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-180}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:3._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-160}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:4._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-140}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:5._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-120}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:6._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-100}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:7._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-80}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:8._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-60}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:9._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-40}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:10._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-20}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:11._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:0}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:12._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:20}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:13._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:40}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:14._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:60}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:15._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:80}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:16._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:100}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:17._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:120}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:18._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:140}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:19._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:160}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:20._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:180}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:21._at: }{space 0}{lalign 16:MYVAR} = {res:{ralign 9:200}}
{lalign 8:}{space 0}{lalign 16:dist_nat_gap_~al} = {res:{ralign 9:-2.739625}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2}  .000086{col 26}{space 2} .0001304{col 37}{space 1}    0.66{col 46}{space 3}0.509{col 54}{space 4}-.0001695{col 67}{space 3} .0003416
{txt}{space 10}2  {c |}{col 14}{res}{space 2}  .000163{col 26}{space 2} .0002247{col 37}{space 1}    0.73{col 46}{space 3}0.468{col 54}{space 4}-.0002774{col 67}{space 3} .0006033
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0003087{col 26}{space 2} .0003833{col 37}{space 1}    0.81{col 46}{space 3}0.421{col 54}{space 4}-.0004426{col 67}{space 3} .0010599
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0005845{col 26}{space 2}  .000646{col 37}{space 1}    0.90{col 46}{space 3}0.366{col 54}{space 4}-.0006815{col 67}{space 3} .0018506
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .0011067{col 26}{space 2} .0010718{col 37}{space 1}    1.03{col 46}{space 3}0.302{col 54}{space 4} -.000994{col 67}{space 3} .0032075
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .0020945{col 26}{space 2} .0017425{col 37}{space 1}    1.20{col 46}{space 3}0.229{col 54}{space 4}-.0013208{col 67}{space 3} .0055098
{txt}{space 10}7  {c |}{col 14}{res}{space 2} .0039603{col 26}{space 2} .0027556{col 37}{space 1}    1.44{col 46}{space 3}0.151{col 54}{space 4}-.0014405{col 67}{space 3} .0093612
{txt}{space 10}8  {c |}{col 14}{res}{space 2} .0074758{col 26}{space 2} .0041892{col 37}{space 1}    1.78{col 46}{space 3}0.074{col 54}{space 4}-.0007348{col 67}{space 3} .0156865
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .0140679{col 26}{space 2} .0060034{col 37}{space 1}    2.34{col 46}{space 3}0.019{col 54}{space 4} .0023015{col 67}{space 3} .0258342
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .0263185{col 26}{space 2} .0078466{col 37}{space 1}    3.35{col 46}{space 3}0.001{col 54}{space 4} .0109394{col 67}{space 3} .0416976
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .0487103{col 26}{space 2} .0090328{col 37}{space 1}    5.39{col 46}{space 3}0.000{col 54}{space 4} .0310063{col 67}{space 3} .0664142
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .0884228{col 26}{space 2} .0114183{col 37}{space 1}    7.74{col 46}{space 3}0.000{col 54}{space 4} .0660433{col 67}{space 3} .1108023
{txt}{space 9}13  {c |}{col 14}{res}{space 2}  .155229{col 26}{space 2} .0262138{col 37}{space 1}    5.92{col 46}{space 3}0.000{col 54}{space 4} .1038508{col 67}{space 3} .2066071
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .2582121{col 26}{space 2} .0598634{col 37}{space 1}    4.31{col 46}{space 3}0.000{col 54}{space 4}  .140882{col 67}{space 3} .3755422
{txt}{space 9}15  {c |}{col 14}{res}{space 2} .3973785{col 26}{space 2} .1052648{col 37}{space 1}    3.78{col 46}{space 3}0.000{col 54}{space 4} .1910634{col 67}{space 3} .6036936
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .5553922{col 26}{space 2} .1411187{col 37}{space 1}    3.94{col 46}{space 3}0.000{col 54}{space 4} .2788047{col 67}{space 3} .8319797
{txt}{space 9}17  {c |}{col 14}{res}{space 2} .7029456{col 26}{space 2} .1473276{col 37}{space 1}    4.77{col 46}{space 3}0.000{col 54}{space 4} .4141888{col 67}{space 3} .9917024
{txt}{space 9}18  {c |}{col 14}{res}{space 2} .8176112{col 26}{space 2} .1253719{col 37}{space 1}    6.52{col 46}{space 3}0.000{col 54}{space 4} .5718869{col 67}{space 3} 1.063336
{txt}{space 9}19  {c |}{col 14}{res}{space 2} .8946485{col 26}{space 2} .0920435{col 37}{space 1}    9.72{col 46}{space 3}0.000{col 54}{space 4} .7142466{col 67}{space 3}  1.07505
{txt}{space 9}20  {c |}{col 14}{res}{space 2} .9414759{col 26}{space 2} .0613148{col 37}{space 1}   15.35{col 46}{space 3}0.000{col 54}{space 4} .8213011{col 67}{space 3} 1.061651
{txt}{space 9}21  {c |}{col 14}{res}{space 2} .9682283{col 26}{space 2} .0384325{col 37}{space 1}   25.19{col 46}{space 3}0.000{col 54}{space 4}  .892902{col 67}{space 3} 1.043555
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
(file {bf}
file1.dta{rm}
not found)
{p_end}

{com}. 
. drop MYVAR
{txt}
{com}. gen MYVAR = dist_nat_gap_criminal
{txt}(102 missing values generated)

{com}. xtlogit _d dist_nat_gap_civil MYVAR  litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-231.18192}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-215.47978}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-214.55355}  
Iteration 4:{space 2}Log pseudolikelihood = {res: -214.5509}  
Iteration 5:{space 2}Log pseudolikelihood = {res: -214.5509}  
{res}
{txt}Fitting full model:

tau = {res} 0.0    {txt}Log pseudolikelihood = {res} -214.5509
{txt}tau = {res} 0.1    {txt}Log pseudolikelihood = {res}-216.78233

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-216.78233}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-214.57362}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-214.55526}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-214.55168}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-214.55108}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-214.55094}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-214.55093}  
Iteration 7:{space 2}Log pseudolikelihood = {res:-214.55092}  
{res}
{txt}Calculating robust standard errors ...

{col 1}Random-effects logistic regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:15})}{col 70} = {res}{ralign 6:62.93}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-214.55092}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0319441{col 40}{space 2} .0068762{col 51}{space 1}    4.65{col 60}{space 3}0.000{col 68}{space 4} .0184669{col 81}{space 3} .0454213
{txt}{space 21}MYVAR {c |}{col 28}{res}{space 2}-.0056994{col 40}{space 2} .0024386{col 51}{space 1}   -2.34{col 60}{space 3}0.019{col 68}{space 4}-.0104791{col 81}{space 3}-.0009197
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .002176{col 40}{space 2} .0164157{col 51}{space 1}    0.13{col 60}{space 3}0.895{col 68}{space 4}-.0299982{col 81}{space 3} .0343503
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.599863{col 40}{space 2} .8176381{col 51}{space 1}   -1.96{col 60}{space 3}0.050{col 68}{space 4}-3.202404{col 81}{space 3} .0026783
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0099819{col 40}{space 2} .0247148{col 51}{space 1}   -0.40{col 60}{space 3}0.686{col 68}{space 4} -.058422{col 81}{space 3} .0384582
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0338828{col 40}{space 2} .0190508{col 51}{space 1}    1.78{col 60}{space 3}0.075{col 68}{space 4}-.0034561{col 81}{space 3} .0712218
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}  2.23832{col 40}{space 2} .5338065{col 51}{space 1}    4.19{col 60}{space 3}0.000{col 68}{space 4} 1.192078{col 81}{space 3} 3.284561
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.3903389{col 40}{space 2} .1290858{col 51}{space 1}   -3.02{col 60}{space 3}0.002{col 68}{space 4}-.6433424{col 81}{space 3}-.1373353
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} -2.89544{col 40}{space 2}  2.35926{col 51}{space 1}   -1.23{col 60}{space 3}0.220{col 68}{space 4}-7.519505{col 81}{space 3} 1.728625
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.4714863{col 40}{space 2} .4502807{col 51}{space 1}   -1.05{col 60}{space 3}0.295{col 68}{space 4} -1.35402{col 81}{space 3} .4110476
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.7090181{col 40}{space 2}  .555086{col 51}{space 1}   -1.28{col 60}{space 3}0.201{col 68}{space 4}-1.796967{col 81}{space 3} .3789305
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.1747052{col 40}{space 2} .3757913{col 51}{space 1}   -0.46{col 60}{space 3}0.642{col 68}{space 4}-.9112426{col 81}{space 3} .5618323
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.1141763{col 40}{space 2}  .332951{col 51}{space 1}   -0.34{col 60}{space 3}0.732{col 68}{space 4}-.7667482{col 81}{space 3} .5383957
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.184415{col 40}{space 2} .5815769{col 51}{space 1}    2.04{col 60}{space 3}0.042{col 68}{space 4} .0445453{col 81}{space 3} 2.324285
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.616854{col 40}{space 2} .9178238{col 51}{space 1}    1.76{col 60}{space 3}0.078{col 68}{space 4}-.1820476{col 81}{space 3} 3.415756
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} -25.3392{col 40}{space 2} 7.269554{col 51}{space 1}   -3.49{col 60}{space 3}0.000{col 68}{space 4}-39.58727{col 81}{space 3}-11.09114
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2} -14.0844{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0008742{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 2.32e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. margins, atmeans at(MYVAR=(-200(20)200)) saving(file2, replace)
{res}
{txt}{col 1}Adjusted predictions{col 60}{lalign 13:Number of obs}{col 73} = {res}{ralign 3:876}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Pr(_d=1), predict(pr)}{p_end}
{p2colreset}{...}
{lalign 8:1._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-200}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:2._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-180}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:3._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-160}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:4._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-140}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:5._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-120}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:6._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-100}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:7._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-80}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:8._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-60}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:9._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-40}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:10._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:-20}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:11._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:0}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:12._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:20}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:13._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:40}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:14._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:60}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:15._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:80}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:16._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:100}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:17._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:120}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:18._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:140}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:19._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:160}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:20._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:180}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}
{lalign 8:21._at: }{space 0}{lalign 16:dist_nat_gap_~il} = {res:{ralign 9:-6.326296}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:MYVAR} = {res:{ralign 9:200}}
{lalign 8:}{space 0}{lalign 16:litrate_1991_2~P} = {res:{ralign 9:.4655335}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:road_density_GAP} = {res:{ralign 9:.0114313}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:lifeexp_1990_2~P} = {res:{ralign 9:.3013079}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:percent_votes1~P} = {res:{ralign 9:.1382067}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_pop} = {res:{ralign 9:12.27733}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:ln_abs_total2001} = {res:{ralign 9:8.615499}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:cast_eth_fract} = {res:{ralign 9:.7959034}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_east} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_mid} = {res:{ralign 9:.2614155}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_west} = {res:{ralign 9:.2248858}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:region_farwest} = {res:{ralign 9:.1175799}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:hilli_region} = {res:{ralign 9:.5136986}} {txt:(mean)}
{lalign 8:}{space 0}{lalign 16:mountain_region} = {res:{ralign 9:.1792237}} {txt:(mean)}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .1140775{col 26}{space 2}  .052627{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} .0109305{col 67}{space 3} .2172245
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .1030543{col 26}{space 2} .0441183{col 37}{space 1}    2.34{col 46}{space 3}0.019{col 54}{space 4}  .016584{col 67}{space 3} .1895246
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0929845{col 26}{space 2} .0366865{col 37}{space 1}    2.53{col 46}{space 3}0.011{col 54}{space 4} .0210802{col 67}{space 3} .1648887
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0838066{col 26}{space 2} .0302669{col 37}{space 1}    2.77{col 46}{space 3}0.006{col 54}{space 4} .0244845{col 67}{space 3} .1431287
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .0754593{col 26}{space 2} .0247943{col 37}{space 1}    3.04{col 46}{space 3}0.002{col 54}{space 4} .0268633{col 67}{space 3} .1240554
{txt}{space 10}6  {c |}{col 14}{res}{space 2} .0678818{col 26}{space 2} .0202068{col 37}{space 1}    3.36{col 46}{space 3}0.001{col 54}{space 4} .0282772{col 67}{space 3} .1074865
{txt}{space 10}7  {c |}{col 14}{res}{space 2}  .061015{col 26}{space 2} .0164485{col 37}{space 1}    3.71{col 46}{space 3}0.000{col 54}{space 4} .0287765{col 67}{space 3} .0932536
{txt}{space 10}8  {c |}{col 14}{res}{space 2}  .054802{col 26}{space 2} .0134699{col 37}{space 1}    4.07{col 46}{space 3}0.000{col 54}{space 4} .0284016{col 67}{space 3} .0812025
{txt}{space 10}9  {c |}{col 14}{res}{space 2} .0491886{col 26}{space 2} .0112222{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 54}{space 4} .0271935{col 67}{space 3} .0711836
{txt}{space 9}10  {c |}{col 14}{res}{space 2} .0441232{col 26}{space 2} .0096441{col 37}{space 1}    4.58{col 46}{space 3}0.000{col 54}{space 4} .0252211{col 67}{space 3} .0630254
{txt}{space 9}11  {c |}{col 14}{res}{space 2} .0395578{col 26}{space 2} .0086433{col 37}{space 1}    4.58{col 46}{space 3}0.000{col 54}{space 4} .0226172{col 67}{space 3} .0564984
{txt}{space 9}12  {c |}{col 14}{res}{space 2} .0354473{col 26}{space 2} .0080897{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 54}{space 4} .0195918{col 67}{space 3} .0513027
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .0317497{col 26}{space 2} .0078355{col 37}{space 1}    4.05{col 46}{space 3}0.000{col 54}{space 4} .0163924{col 67}{space 3} .0471071
{txt}{space 9}14  {c |}{col 14}{res}{space 2} .0284265{col 26}{space 2} .0077483{col 37}{space 1}    3.67{col 46}{space 3}0.000{col 54}{space 4} .0132402{col 67}{space 3} .0436129
{txt}{space 9}15  {c |}{col 14}{res}{space 2}  .025442{col 26}{space 2} .0077305{col 37}{space 1}    3.29{col 46}{space 3}0.001{col 54}{space 4} .0102906{col 67}{space 3} .0405934
{txt}{space 9}16  {c |}{col 14}{res}{space 2} .0227635{col 26}{space 2} .0077208{col 37}{space 1}    2.95{col 46}{space 3}0.003{col 54}{space 4} .0076309{col 67}{space 3} .0378961
{txt}{space 9}17  {c |}{col 14}{res}{space 2} .0203611{col 26}{space 2} .0076859{col 37}{space 1}    2.65{col 46}{space 3}0.008{col 54}{space 4} .0052969{col 67}{space 3} .0354252
{txt}{space 9}18  {c |}{col 14}{res}{space 2} .0182075{col 26}{space 2} .0076104{col 37}{space 1}    2.39{col 46}{space 3}0.017{col 54}{space 4} .0032914{col 67}{space 3} .0331236
{txt}{space 9}19  {c |}{col 14}{res}{space 2} .0162779{col 26}{space 2} .0074898{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} .0015981{col 67}{space 3} .0309577
{txt}{space 9}20  {c |}{col 14}{res}{space 2} .0145498{col 26}{space 2}  .007326{col 37}{space 1}    1.99{col 46}{space 3}0.047{col 54}{space 4} .0001911{col 67}{space 3} .0289084
{txt}{space 9}21  {c |}{col 14}{res}{space 2} .0130027{col 26}{space 2} .0071236{col 37}{space 1}    1.83{col 46}{space 3}0.068{col 54}{space 4}-.0009594{col 67}{space 3} .0269648
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
(file {bf}
file2.dta{rm}
not found)
{p_end}

{com}.  
. combomarginsplot file1 file2, labels("Change in civil cases" "Change in criminal cases") xtitle("")
{txt}Warning: statistics differ for {res}dist_nat_gap_criminal{txt}: file {res}1{txt}={res}mean{txt}, file {res}2{txt}={res}asobserved{txt};  using first ({res}mean{txt})
{res}
{text}{p 2 6 2}Variables that uniquely identify margins: MYVAR _filenumber{p_end}
{res}{txt}
{com}. 
. drop MYVAR
{txt}
{com}. 
. //Model 4 probit
. xtprobit _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  hilli_region mountain_region  if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res: -230.1681}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-218.25231}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-218.03567}  
Iteration 4:{space 2}Log pseudolikelihood = {res: -218.0356}  
Iteration 5:{space 2}Log pseudolikelihood = {res: -218.0356}  
{res}
{txt}Fitting full model:

rho = {res} 0.0    {txt}Log pseudolikelihood = {res} -218.0356
{txt}rho = {res} 0.1    {txt}Log pseudolikelihood = {res}-226.32806

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-226.32806}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-218.23094}  
Iteration 2:{space 2}Log pseudolikelihood = {res: -218.0427}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-218.03642}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-218.03573}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-218.03562}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-218.03561}  
{res}
{txt}Calculating robust standard errors ...
{res}
{txt}{col 1}Random-effects probit regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:10})}{col 70} = {res}{ralign 6:51.09}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-218.03561}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0151086{col 40}{space 2}   .00353{col 51}{space 1}    4.28{col 60}{space 3}0.000{col 68}{space 4} .0081899{col 81}{space 3} .0220273
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0031211{col 40}{space 2} .0013193{col 51}{space 1}   -2.37{col 60}{space 3}0.018{col 68}{space 4}-.0057068{col 81}{space 3}-.0005354
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0022676{col 40}{space 2} .0062203{col 51}{space 1}    0.36{col 60}{space 3}0.715{col 68}{space 4} -.009924{col 81}{space 3} .0144592
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.6615867{col 40}{space 2} .2902448{col 51}{space 1}   -2.28{col 60}{space 3}0.023{col 68}{space 4}-1.230456{col 81}{space 3}-.0927173
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0242366{col 40}{space 2} .0091117{col 51}{space 1}   -2.66{col 60}{space 3}0.008{col 68}{space 4}-.0420952{col 81}{space 3}-.0063779
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0156114{col 40}{space 2} .0085392{col 51}{space 1}    1.83{col 60}{space 3}0.068{col 68}{space 4} -.001125{col 81}{space 3} .0323479
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .8273876{col 40}{space 2}  .230371{col 51}{space 1}    3.59{col 60}{space 3}0.000{col 68}{space 4} .3758688{col 81}{space 3} 1.278906
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.1345598{col 40}{space 2} .0505367{col 51}{space 1}   -2.66{col 60}{space 3}0.008{col 68}{space 4}-.2336099{col 81}{space 3}-.0355096
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} .5188005{col 40}{space 2} .2172208{col 51}{space 1}    2.39{col 60}{space 3}0.017{col 68}{space 4} .0930556{col 81}{space 3} .9445454
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} .6251536{col 40}{space 2} .3442932{col 51}{space 1}    1.82{col 60}{space 3}0.069{col 68}{space 4}-.0496485{col 81}{space 3} 1.299956
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-10.97612{col 40}{space 2} 2.910181{col 51}{space 1}   -3.77{col 60}{space 3}0.000{col 68}{space 4}-16.67997{col 81}{space 3}-5.272272
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2}-15.76693{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0003769{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 1.42e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_d]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_d]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_d]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_d]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_d]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_d]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_d]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_d]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_d]hilli_region = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_d]mountain_region = 0{p_end}

           {txt}chi2( 10) ={res}   51.09
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}.  //Model 5 probit
.  xtprobit _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-232.95087}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-220.82517}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-220.24138}  
Iteration 4:{space 2}Log pseudolikelihood = {res: -220.2403}  
Iteration 5:{space 2}Log pseudolikelihood = {res: -220.2403}  
{res}
{txt}Fitting full model:

rho = {res} 0.0    {txt}Log pseudolikelihood = {res} -220.2403
{txt}rho = {res} 0.1    {txt}Log pseudolikelihood = {res}-229.04931

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-229.04931}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-220.43864}  
Iteration 2:{space 2}Log pseudolikelihood = {res: -220.2473}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-220.24117}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-220.24043}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-220.24032}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-220.24032}  
{res}
{txt}Calculating robust standard errors ...
{res}
{txt}{col 1}Random-effects probit regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:12})}{col 70} = {res}{ralign 6:59.44}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-220.24032}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}  .015618{col 40}{space 2} .0035505{col 51}{space 1}    4.40{col 60}{space 3}0.000{col 68}{space 4} .0086591{col 81}{space 3} .0225769
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0027524{col 40}{space 2} .0012944{col 51}{space 1}   -2.13{col 60}{space 3}0.033{col 68}{space 4}-.0052894{col 81}{space 3}-.0002155
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0094754{col 40}{space 2} .0066632{col 51}{space 1}    1.42{col 60}{space 3}0.155{col 68}{space 4}-.0035842{col 81}{space 3} .0225351
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.6435052{col 40}{space 2} .3592266{col 51}{space 1}   -1.79{col 60}{space 3}0.073{col 68}{space 4}-1.347576{col 81}{space 3}  .060566
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0141506{col 40}{space 2} .0116035{col 51}{space 1}   -1.22{col 60}{space 3}0.223{col 68}{space 4}-.0368931{col 81}{space 3} .0085919
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0041773{col 40}{space 2}  .006446{col 51}{space 1}    0.65{col 60}{space 3}0.517{col 68}{space 4}-.0084566{col 81}{space 3} .0168111
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .6182274{col 40}{space 2} .1093631{col 51}{space 1}    5.65{col 60}{space 3}0.000{col 68}{space 4} .4038797{col 81}{space 3} .8325752
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.1776411{col 40}{space 2} .0491538{col 51}{space 1}   -3.61{col 60}{space 3}0.000{col 68}{space 4}-.2739808{col 81}{space 3}-.0813014
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.2058337{col 40}{space 2} .1430107{col 51}{space 1}   -1.44{col 60}{space 3}0.150{col 68}{space 4}-.4861296{col 81}{space 3} .0744621
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} -.214858{col 40}{space 2} .1522157{col 51}{space 1}   -1.41{col 60}{space 3}0.158{col 68}{space 4}-.5131954{col 81}{space 3} .0834793
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}  -.07419{col 40}{space 2} .1437407{col 51}{space 1}   -0.52{col 60}{space 3}0.606{col 68}{space 4}-.3559166{col 81}{space 3} .2075366
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .0386896{col 40}{space 2} .1137798{col 51}{space 1}    0.34{col 60}{space 3}0.734{col 68}{space 4}-.1843147{col 81}{space 3} .2616939
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-7.520043{col 40}{space 2}  1.12989{col 51}{space 1}   -6.66{col 60}{space 3}0.000{col 68}{space 4}-9.734588{col 81}{space 3}-5.305498
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2}-15.85226{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0003612{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 1.30e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_d]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_d]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_d]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_d]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_d]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_d]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_d]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_d]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_d]region_east = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_d]region_mid = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} [_d]region_west = 0{p_end}
{p 0 7}{space 1}{text:(12)}{space 1} [_d]region_farwest = 0{p_end}

           {txt}chi2( 12) ={res}   59.44
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}. //Model 6 Probit
. xtprobit _d dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, vce(robust)

{txt}Fitting comparison model:

{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-246.44239}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-228.96354}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-216.14478}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-215.75495}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-215.75458}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-215.75458}  
{res}
{txt}Fitting full model:

rho = {res} 0.0    {txt}Log pseudolikelihood = {res}-215.75458
{txt}rho = {res} 0.1    {txt}Log pseudolikelihood = {res}-223.73351

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-223.73351}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-216.08653}  
Iteration 2:{space 2}Log pseudolikelihood = {res:  -215.762}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-215.75591}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-215.75489}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-215.75464}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-215.75459}  
Iteration 7:{space 2}Log pseudolikelihood = {res:-215.75459}  
{res}
{txt}Calculating robust standard errors ...
{res}
{txt}{col 1}Random-effects probit regression{col 54}{lalign 16:Number of obs}{col 70} = {res}{ralign 6:876}
{txt}{col 1}{txt}Group variable: {res}sno{txt}{col 54}{lalign 16:Number of groups}{col 70} = {res}{ralign 6:75}

{txt}{col 1}Random effects u_i ~ {txt:Gaussian}{col 54}Obs per group:
{col 54}{ralign 16:min}{col 70} = {res}{ralign 6:6}
{txt}{col 54}{ralign 16:avg}{col 70} = {res}{ralign 6:11.7}
{txt}{col 54}{ralign 16:max}{col 70} = {res}{ralign 6:15}

{txt}{col 1}Integration method: {res:mvaghermite}{col 54}{lalign 16:Integration pts.}{col 70} = {res}{ralign 6:12}

{txt}{col 54}{lalign 16:Wald chi2({res:15})}{col 70} = {res}{ralign 6:66.75}
{txt}{col 1}{lalign 20:Log pseudolikelihood}{col 21} = {res}{ralign 10:-215.75459}{txt}{col 54}{lalign 16:Prob > chi2}{col 70} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _d{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0155458{col 40}{space 2} .0035346{col 51}{space 1}    4.40{col 60}{space 3}0.000{col 68}{space 4} .0086181{col 81}{space 3} .0224734
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0032638{col 40}{space 2} .0013604{col 51}{space 1}   -2.40{col 60}{space 3}0.016{col 68}{space 4}-.0059301{col 81}{space 3}-.0005976
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0006561{col 40}{space 2} .0074975{col 51}{space 1}    0.09{col 60}{space 3}0.930{col 68}{space 4}-.0140388{col 81}{space 3} .0153511
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.8649415{col 40}{space 2} .3952597{col 51}{space 1}   -2.19{col 60}{space 3}0.029{col 68}{space 4}-1.639636{col 81}{space 3}-.0902466
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0065821{col 40}{space 2} .0122328{col 51}{space 1}   -0.54{col 60}{space 3}0.591{col 68}{space 4}-.0305579{col 81}{space 3} .0173938
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0179854{col 40}{space 2} .0094076{col 51}{space 1}    1.91{col 60}{space 3}0.056{col 68}{space 4}-.0004532{col 81}{space 3}  .036424
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.064277{col 40}{space 2} .2229097{col 51}{space 1}    4.77{col 60}{space 3}0.000{col 68}{space 4}  .627382{col 81}{space 3} 1.501172
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.1980369{col 40}{space 2} .0633871{col 51}{space 1}   -3.12{col 60}{space 3}0.002{col 68}{space 4}-.3222734{col 81}{space 3}-.0738004
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}-2.137509{col 40}{space 2} 1.131254{col 51}{space 1}   -1.89{col 60}{space 3}0.059{col 68}{space 4}-4.354727{col 81}{space 3} .0797084
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.1145452{col 40}{space 2} .2050604{col 51}{space 1}   -0.56{col 60}{space 3}0.576{col 68}{space 4}-.5164561{col 81}{space 3} .2873657
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.2124724{col 40}{space 2} .2337935{col 51}{space 1}   -0.91{col 60}{space 3}0.363{col 68}{space 4}-.6706992{col 81}{space 3} .2457544
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.0095801{col 40}{space 2} .1749277{col 51}{space 1}   -0.05{col 60}{space 3}0.956{col 68}{space 4}-.3524321{col 81}{space 3}  .333272
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.0651372{col 40}{space 2} .1550606{col 51}{space 1}   -0.42{col 60}{space 3}0.674{col 68}{space 4}-.3690505{col 81}{space 3}  .238776
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} .4899526{col 40}{space 2} .2394216{col 51}{space 1}    2.05{col 60}{space 3}0.041{col 68}{space 4} .0206949{col 81}{space 3} .9592102
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} .6041784{col 40}{space 2} .3654102{col 51}{space 1}    1.65{col 60}{space 3}0.098{col 68}{space 4}-.1120125{col 81}{space 3} 1.320369
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-11.55067{col 40}{space 2} 2.914461{col 51}{space 1}   -3.96{col 60}{space 3}0.000{col 68}{space 4}-17.26291{col 81}{space 3}-5.838432
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsig2u {c |}{col 28}{res}{space 2}-16.07863{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |}{col 28}{res}{space 2} .0003225{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}                       rho {c |}{col 28}{res}{space 2} 1.04e-07{col 40}{space 2}        .{col 68}{space 4}        .{col 81}{space 3}        .
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  test

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[_d]dist_nat_gap_civil = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [_d]dist_nat_gap_criminal = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [_d]litrate_1991_2001_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [_d]road_density_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [_d]lifeexp_1990_2011_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [_d]percent_votes1991_1999_GAP = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [_d]ln_pop = 0{p_end}
{p 0 7}{space 1}{text:( 8)}{space 1} [_d]ln_abs_total2001 = 0{p_end}
{p 0 7}{space 1}{text:( 9)}{space 1} [_d]cast_eth_fract = 0{p_end}
{p 0 7}{space 1}{text:(10)}{space 1} [_d]region_east = 0{p_end}
{p 0 7}{space 1}{text:(11)}{space 1} [_d]region_mid = 0{p_end}
{p 0 7}{space 1}{text:(12)}{space 1} [_d]region_west = 0{p_end}
{p 0 7}{space 1}{text:(13)}{space 1} [_d]region_farwest = 0{p_end}
{p 0 7}{space 1}{text:(14)}{space 1} [_d]hilli_region = 0{p_end}
{p 0 7}{space 1}{text:(15)}{space 1} [_d]mountain_region = 0{p_end}

           {txt}chi2( 15) ={res}   66.75
         {txt}Prob > chi2 ={res}    0.0000

{txt}
{com}.  
. //Model Selection Statistics
.  //COX
.  
.  //Model 1
. stcox dist_nat_gap_civil dist_nat_gap_criminal if sample ==1, cluster (sn)

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:  Log pseudolikelihood = {res}-271.74056
{txt}Iteration 1:  Log pseudolikelihood = {res}-270.04981
{txt}Iteration 2:  Log pseudolikelihood = {res}-269.23302
{txt}Iteration 3:  Log pseudolikelihood = {res}-269.21696
{txt}Iteration 4:  Log pseudolikelihood = {res}-269.21693
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-269.21693

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:2})} = {res}{ralign 6:10.86}
{txt}Log pseudolikelihood = {res}-269.21693{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0044}

{txt}{ralign 87:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                   _t{col 23}{c |} Haz. ratio{col 35}   std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}dist_nat_gap_civil {c |}{col 23}{res}{space 2} 1.006641{col 35}{space 2} .0030999{col 46}{space 1}    2.15{col 55}{space 3}0.032{col 63}{space 4} 1.000584{col 76}{space 3} 1.012735
{txt}dist_nat_gap_criminal {c |}{col 23}{res}{space 2} .9957374{col 35}{space 2} .0013575{col 46}{space 1}   -3.13{col 55}{space 3}0.002{col 63}{space 4} .9930803{col 76}{space 3} .9984016
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-271.7406{col 39}-269.2169{col 50}     2{col 58} 542.4339{col 69} 551.9846
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. // Model 2
.  
. stcox dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP if sample ==1, cluster (sn)

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:  Log pseudolikelihood = {res}-271.74056
{txt}Iteration 1:  Log pseudolikelihood = {res}-268.63619
{txt}Iteration 2:  Log pseudolikelihood = {res}-267.36207
{txt}Iteration 3:  Log pseudolikelihood = {res}-267.33617
{txt}Iteration 4:  Log pseudolikelihood = {res}-267.33611
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-267.33611

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:6})} = {res}{ralign 6:21.66}
{txt}Log pseudolikelihood = {res}-267.33611{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0014}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. ratio{col 40}   std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} 1.005555{col 40}{space 2} .0025499{col 51}{space 1}    2.18{col 60}{space 3}0.029{col 68}{space 4}  1.00057{col 81}{space 3} 1.010565
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .9963012{col 40}{space 2} .0013437{col 51}{space 1}   -2.75{col 60}{space 3}0.006{col 68}{space 4} .9936711{col 81}{space 3} .9989384
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .9978371{col 40}{space 2} .0086502{col 51}{space 1}   -0.25{col 60}{space 3}0.803{col 68}{space 4} .9810262{col 81}{space 3} 1.014936
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .6545659{col 40}{space 2} .3445066{col 51}{space 1}   -0.81{col 60}{space 3}0.421{col 68}{space 4} .2333216{col 81}{space 3} 1.836335
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .9755735{col 40}{space 2} .0178788{col 51}{space 1}   -1.35{col 60}{space 3}0.177{col 68}{space 4} .9411536{col 81}{space 3} 1.011252
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} 1.006345{col 40}{space 2} .0122576{col 51}{space 1}    0.52{col 60}{space 3}0.604{col 68}{space 4}  .982605{col 81}{space 3} 1.030659
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-271.7406{col 39}-267.3361{col 50}     6{col 58} 546.6722{col 69} 575.3244
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  //Model 3
. stcox dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 if sample ==1, cluster(sn)

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:  Log pseudolikelihood = {res}-271.74056
{txt}Iteration 1:  Log pseudolikelihood = {res}-263.24099
{txt}Iteration 2:  Log pseudolikelihood = {res}-262.14465
{txt}Iteration 3:  Log pseudolikelihood = {res}-262.12155
{txt}Iteration 4:  Log pseudolikelihood = {res}-262.12151
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-262.12151

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:9})} = {res}{ralign 6:33.49}
{txt}Log pseudolikelihood = {res}-262.12151{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0001}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. ratio{col 40}   std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} 1.010325{col 40}{space 2} .0033459{col 51}{space 1}    3.10{col 60}{space 3}0.002{col 68}{space 4} 1.003788{col 81}{space 3} 1.016904
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .9945111{col 40}{space 2}    .0016{col 51}{space 1}   -3.42{col 60}{space 3}0.001{col 68}{space 4} .9913802{col 81}{space 3} .9976519
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .9951437{col 40}{space 2}   .00892{col 51}{space 1}   -0.54{col 60}{space 3}0.587{col 68}{space 4} .9778134{col 81}{space 3} 1.012781
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}   .27088{col 40}{space 2} .2610405{col 51}{space 1}   -1.36{col 60}{space 3}0.175{col 68}{space 4} .0409727{col 81}{space 3} 1.790851
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .9666043{col 40}{space 2} .0191519{col 51}{space 1}   -1.71{col 60}{space 3}0.086{col 68}{space 4} .9297869{col 81}{space 3}  1.00488
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .9974813{col 40}{space 2} .0118891{col 51}{space 1}   -0.21{col 60}{space 3}0.832{col 68}{space 4} .9744492{col 81}{space 3} 1.021058
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} .1321133{col 40}{space 2} .1645836{col 51}{space 1}   -1.62{col 60}{space 3}0.104{col 68}{space 4} .0114958{col 81}{space 3} 1.518283
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 2.072425{col 40}{space 2} .4906679{col 51}{space 1}    3.08{col 60}{space 3}0.002{col 68}{space 4} 1.303011{col 81}{space 3}  3.29617
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .9482511{col 40}{space 2} .1145855{col 51}{space 1}   -0.44{col 60}{space 3}0.660{col 68}{space 4} .7482818{col 81}{space 3}  1.20166
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-271.7406{col 39}-262.1215{col 50}     9{col 58}  542.243{col 69} 585.2213
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. //Model 4
. stcox dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  if sample ==1, cluster(sn)  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:  Log pseudolikelihood = {res}-271.74056
{txt}Iteration 1:  Log pseudolikelihood = {res}-260.55561
{txt}Iteration 2:  Log pseudolikelihood = {res}-259.18296
{txt}Iteration 3:  Log pseudolikelihood = {res}-259.15195
{txt}Iteration 4:  Log pseudolikelihood = {res}-259.15186
{txt}Iteration 5:  Log pseudolikelihood = {res}-259.15186
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-259.15186

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:10})} = {res}{ralign 6:42.25}
{txt}Log pseudolikelihood = {res}-259.15186{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. ratio{col 40}   std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} 1.007466{col 40}{space 2} .0035772{col 51}{space 1}    2.09{col 60}{space 3}0.036{col 68}{space 4} 1.000479{col 81}{space 3} 1.014502
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .9947833{col 40}{space 2} .0017109{col 51}{space 1}   -3.04{col 60}{space 3}0.002{col 68}{space 4} .9914357{col 81}{space 3} .9981421
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .9901838{col 40}{space 2} .0093782{col 51}{space 1}   -1.04{col 60}{space 3}0.298{col 68}{space 4} .9719725{col 81}{space 3} 1.008736
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .3581264{col 40}{space 2} .2669464{col 51}{space 1}   -1.38{col 60}{space 3}0.168{col 68}{space 4} .0830908{col 81}{space 3} 1.543546
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .9433384{col 40}{space 2} .0174076{col 51}{space 1}   -3.16{col 60}{space 3}0.002{col 68}{space 4} .9098297{col 81}{space 3} .9780813
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} 1.002478{col 40}{space 2} .0113206{col 51}{space 1}    0.22{col 60}{space 3}0.827{col 68}{space 4}  .980534{col 81}{space 3} 1.024914
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 2.249034{col 40}{space 2} .5079954{col 51}{space 1}    3.59{col 60}{space 3}0.000{col 68}{space 4} 1.444551{col 81}{space 3} 3.501541
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .9086061{col 40}{space 2} .1019793{col 51}{space 1}   -0.85{col 60}{space 3}0.393{col 68}{space 4} .7291875{col 81}{space 3} 1.132171
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 2.643177{col 40}{space 2} .7361374{col 51}{space 1}    3.49{col 60}{space 3}0.000{col 68}{space 4} 1.531308{col 81}{space 3} 4.562364
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.921041{col 40}{space 2} .7249078{col 51}{space 1}    1.73{col 60}{space 3}0.084{col 68}{space 4} .9169263{col 81}{space 3} 4.024749
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-271.7406{col 39}-259.1519{col 50}    10{col 58} 538.3037{col 69} 586.0574
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 5
. stcox dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, cluster(sn) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:  Log pseudolikelihood = {res}-271.74056
{txt}Iteration 1:  Log pseudolikelihood = {res}-261.38266
{txt}Iteration 2:  Log pseudolikelihood = {res}-259.15114
{txt}Iteration 3:  Log pseudolikelihood = {res}-259.12141
{txt}Iteration 4:  Log pseudolikelihood = {res}-259.12136
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-259.12136

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:12})} = {res}{ralign 6:45.20}
{txt}Log pseudolikelihood = {res}-259.12136{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. ratio{col 40}   std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} 1.009335{col 40}{space 2} .0035181{col 51}{space 1}    2.67{col 60}{space 3}0.008{col 68}{space 4} 1.002463{col 81}{space 3} 1.016254
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .9955548{col 40}{space 2} .0016307{col 51}{space 1}   -2.72{col 60}{space 3}0.007{col 68}{space 4} .9923638{col 81}{space 3} .9987561
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} 1.005014{col 40}{space 2} .0093332{col 51}{space 1}    0.54{col 60}{space 3}0.590{col 68}{space 4} .9868866{col 81}{space 3} 1.023474
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .2694995{col 40}{space 2} .2873958{col 51}{space 1}   -1.23{col 60}{space 3}0.219{col 68}{space 4} .0333297{col 81}{space 3} 2.179136
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .9756594{col 40}{space 2}  .021236{col 51}{space 1}   -1.13{col 60}{space 3}0.258{col 68}{space 4} .9349128{col 81}{space 3} 1.018182
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .9892355{col 40}{space 2} .0127515{col 51}{space 1}   -0.84{col 60}{space 3}0.401{col 68}{space 4} .9645561{col 81}{space 3} 1.014546
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.732351{col 40}{space 2} .4100686{col 51}{space 1}    2.32{col 60}{space 3}0.020{col 68}{space 4} 1.089296{col 81}{space 3} 2.755026
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} 1.022011{col 40}{space 2}  .153736{col 51}{space 1}    0.14{col 60}{space 3}0.885{col 68}{space 4} .7610509{col 81}{space 3} 1.372453
{txt}{space 15}region_east {c |}{col 28}{res}{space 2} .3333252{col 40}{space 2} .1174951{col 51}{space 1}   -3.12{col 60}{space 3}0.002{col 68}{space 4} .1670417{col 81}{space 3} .6651375
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} .4059353{col 40}{space 2}  .135583{col 51}{space 1}   -2.70{col 60}{space 3}0.007{col 68}{space 4} .2109376{col 81}{space 3} .7811951
{txt}{space 15}region_west {c |}{col 28}{res}{space 2} .2971437{col 40}{space 2} .1222811{col 51}{space 1}   -2.95{col 60}{space 3}0.003{col 68}{space 4} .1326412{col 81}{space 3} .6656633
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .4522127{col 40}{space 2} .1681291{col 51}{space 1}   -2.13{col 60}{space 3}0.033{col 68}{space 4} .2182091{col 81}{space 3} .9371577
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-271.7406{col 39}-259.1214{col 50}    12{col 58} 542.2427{col 69} 599.5471
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 6
. stcox dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001        ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, cluster(sn)  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:  Log pseudolikelihood = {res}-271.74056
{txt}Iteration 1:  Log pseudolikelihood = {res}-257.84475
{txt}Iteration 2:  Log pseudolikelihood = {res}-255.60527
{txt}Iteration 3:  Log pseudolikelihood = {res}-255.55556
{txt}Iteration 4:  Log pseudolikelihood = {res}-255.55534
{txt}Iteration 5:  Log pseudolikelihood = {res}-255.55534
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-255.55534

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:15})} = {res}{ralign 6:59.56}
{txt}Log pseudolikelihood = {res}-255.55534{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. ratio{col 40}   std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} 1.007049{col 40}{space 2} .0037017{col 51}{space 1}    1.91{col 60}{space 3}0.056{col 68}{space 4} .9998202{col 81}{space 3} 1.014331
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .9953544{col 40}{space 2} .0017338{col 51}{space 1}   -2.67{col 60}{space 3}0.008{col 68}{space 4} .9919619{col 81}{space 3} .9987584
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .9960733{col 40}{space 2} .0103012{col 51}{space 1}   -0.38{col 60}{space 3}0.704{col 68}{space 4} .9760867{col 81}{space 3} 1.016469
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .2688445{col 40}{space 2} .2104339{col 51}{space 1}   -1.68{col 60}{space 3}0.093{col 68}{space 4} .0579744{col 81}{space 3} 1.246712
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .9708266{col 40}{space 2} .0212164{col 51}{space 1}   -1.35{col 60}{space 3}0.175{col 68}{space 4} .9301213{col 81}{space 3} 1.013313
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .9933326{col 40}{space 2} .0117873{col 51}{space 1}   -0.56{col 60}{space 3}0.573{col 68}{space 4} .9704966{col 81}{space 3} 1.016706
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}  3.13021{col 40}{space 2} .9138702{col 51}{space 1}    3.91{col 60}{space 3}0.000{col 68}{space 4} 1.766297{col 81}{space 3}  5.54732
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .8614772{col 40}{space 2} .1261831{col 51}{space 1}   -1.02{col 60}{space 3}0.309{col 68}{space 4} .6464959{col 81}{space 3} 1.147947
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} .2173121{col 40}{space 2} .3293914{col 51}{space 1}   -1.01{col 60}{space 3}0.314{col 68}{space 4} .0111397{col 81}{space 3} 4.239308
{txt}{space 15}region_east {c |}{col 28}{res}{space 2} .3397112{col 40}{space 2} .1099657{col 51}{space 1}   -3.34{col 60}{space 3}0.001{col 68}{space 4} .1801245{col 81}{space 3} .6406882
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} .3368816{col 40}{space 2} .1131034{col 51}{space 1}   -3.24{col 60}{space 3}0.001{col 68}{space 4} .1744609{col 81}{space 3} .6505138
{txt}{space 15}region_west {c |}{col 28}{res}{space 2} .3512887{col 40}{space 2} .1368964{col 51}{space 1}   -2.68{col 60}{space 3}0.007{col 68}{space 4} .1636639{col 81}{space 3} .7540071
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}  .403795{col 40}{space 2} .1612071{col 51}{space 1}   -2.27{col 60}{space 3}0.023{col 68}{space 4} .1846442{col 81}{space 3} .8830518
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2}  2.60143{col 40}{space 2} .7401563{col 51}{space 1}    3.36{col 60}{space 3}0.001{col 68}{space 4} 1.489461{col 81}{space 3} 4.543549
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 2.192743{col 40}{space 2} .9199553{col 51}{space 1}    1.87{col 60}{space 3}0.061{col 68}{space 4} .9635404{col 81}{space 3} 4.990056
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  
.  estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-271.7406{col 39}-255.5553{col 50}    15{col 58} 541.1107{col 69} 612.7412
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  //Weibull
.  //Model 1
. streg dist_nat_gap_civil dist_nat_gap_criminal, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 29.718555}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 30.193322}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 30.196194}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 30.196195}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:2})} = {res}{ralign 6:16.43}
{txt}Log pseudolikelihood = {res}30.196195{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0003}

{txt}{ralign 87:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                   _t{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}dist_nat_gap_civil {c |}{col 23}{res}{space 2} .0112014{col 35}{space 2} .0032568{col 46}{space 1}    3.44{col 55}{space 3}0.001{col 63}{space 4} .0048182{col 76}{space 3} .0175846
{txt}dist_nat_gap_criminal {c |}{col 23}{res}{space 2}-.0031898{col 35}{space 2} .0010053{col 46}{space 1}   -3.17{col 55}{space 3}0.002{col 63}{space 4}-.0051601{col 76}{space 3}-.0012195
{txt}{space 16}_cons {c |}{col 23}{res}{space 2}-19.49749{col 35}{space 2} 2.614587{col 46}{space 1}   -7.46{col 55}{space 3}0.000{col 63}{space 4}-24.62199{col 76}{space 3}-14.37299
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/ln_p {c |}{col 23}{res}{space 2} 2.039105{col 35}{space 2} .1353131{col 46}{space 1}   15.07{col 55}{space 3}0.000{col 63}{space 4} 1.773896{col 76}{space 3} 2.304314
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                    p {c |}{col 23}{res}{space 2}  7.68373{col 35}{space 2} 1.039709{col 63}{space 4} 5.893773{col 76}{space 3}  10.0173
{txt}                  1/p {c |}{col 23}{res}{space 2} .1301451{col 35}{space 2} .0176103{col 63}{space 4} .0998273{col 76}{space 3} .1696706
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.95896{col 39}  30.1962{col 50}     4{col 58}-52.39239{col 69}-33.29093
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 2
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 32.261938}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 33.339433}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 33.353625}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 33.353668}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 33.353668}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:6})} = {res}{ralign 6:28.50}
{txt}Log pseudolikelihood = {res}33.353668{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0001}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0107327{col 40}{space 2} .0025527{col 51}{space 1}    4.20{col 60}{space 3}0.000{col 68}{space 4} .0057295{col 81}{space 3} .0157358
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0024053{col 40}{space 2}  .001011{col 51}{space 1}   -2.38{col 60}{space 3}0.017{col 68}{space 4}-.0043867{col 81}{space 3}-.0004239
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0003046{col 40}{space 2} .0144632{col 51}{space 1}   -0.02{col 60}{space 3}0.983{col 68}{space 4}-.0286519{col 81}{space 3} .0280427
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.6632097{col 40}{space 2} .7141645{col 51}{space 1}   -0.93{col 60}{space 3}0.353{col 68}{space 4}-2.062946{col 81}{space 3} .7365271
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}  -.01466{col 40}{space 2} .0254319{col 51}{space 1}   -0.58{col 60}{space 3}0.564{col 68}{space 4}-.0645057{col 81}{space 3} .0351857
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0150637{col 40}{space 2} .0143865{col 51}{space 1}    1.05{col 60}{space 3}0.295{col 68}{space 4}-.0131333{col 81}{space 3} .0432607
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-20.26894{col 40}{space 2}   2.8524{col 51}{space 1}   -7.11{col 60}{space 3}0.000{col 68}{space 4}-25.85954{col 81}{space 3}-14.67834
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.079459{col 40}{space 2} .1412108{col 51}{space 1}   14.73{col 60}{space 3}0.000{col 68}{space 4} 1.802691{col 81}{space 3} 2.356227
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 8.000141{col 40}{space 2} 1.129706{col 68}{space 4}  6.06595{col 81}{space 3} 10.55107
{txt}                       1/p {c |}{col 28}{res}{space 2} .1249978{col 40}{space 2}  .017651{col 68}{space 4} .0947771{col 81}{space 3} .1648546
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.95896{col 39} 33.35367{col 50}     8{col 58}-50.70734{col 69}-12.50441
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 3
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 39.514244}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 45.345468}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 45.516971}  
Iteration 4:{space 2}Log pseudolikelihood = {res:  45.52319}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 45.523201}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 45.523201}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:9})} = {res}{ralign 6:62.04}
{txt}Log pseudolikelihood = {res}45.523201{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0151849{col 40}{space 2} .0034499{col 51}{space 1}    4.40{col 60}{space 3}0.000{col 68}{space 4} .0084233{col 81}{space 3} .0219466
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0054029{col 40}{space 2} .0013264{col 51}{space 1}   -4.07{col 60}{space 3}0.000{col 68}{space 4}-.0080026{col 81}{space 3}-.0028033
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .000358{col 40}{space 2} .0129803{col 51}{space 1}    0.03{col 60}{space 3}0.978{col 68}{space 4} -.025083{col 81}{space 3} .0257989
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-2.147982{col 40}{space 2} 1.433719{col 51}{space 1}   -1.50{col 60}{space 3}0.134{col 68}{space 4} -4.95802{col 81}{space 3} .6620561
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0393576{col 40}{space 2} .0242909{col 51}{space 1}   -1.62{col 60}{space 3}0.105{col 68}{space 4}-.0869669{col 81}{space 3} .0082517
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0030316{col 40}{space 2} .0141817{col 51}{space 1}    0.21{col 60}{space 3}0.831{col 68}{space 4}-.0247641{col 81}{space 3} .0308273
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}-2.958295{col 40}{space 2} 1.558501{col 51}{space 1}   -1.90{col 60}{space 3}0.058{col 68}{space 4}-6.012902{col 81}{space 3} .0963115
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .9568317{col 40}{space 2} .2881563{col 51}{space 1}    3.32{col 60}{space 3}0.001{col 68}{space 4} .3920557{col 81}{space 3} 1.521608
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.0204221{col 40}{space 2} .1479636{col 51}{space 1}   -0.14{col 60}{space 3}0.890{col 68}{space 4}-.3104255{col 81}{space 3} .2695812
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-33.40984{col 40}{space 2} 4.722408{col 51}{space 1}   -7.07{col 60}{space 3}0.000{col 68}{space 4}-42.66559{col 81}{space 3}-24.15409
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.250366{col 40}{space 2} .1533091{col 51}{space 1}   14.68{col 60}{space 3}0.000{col 68}{space 4} 1.949885{col 81}{space 3} 2.550846
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 9.491205{col 40}{space 2} 1.455088{col 68}{space 4} 7.027881{col 81}{space 3} 12.81794
{txt}                       1/p {c |}{col 28}{res}{space 2} .1053607{col 40}{space 2} .0161528{col 68}{space 4} .0780157{col 81}{space 3} .1422904
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.95896{col 39}  45.5232{col 50}    11{col 58} -69.0464{col 69}-16.51738
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
. //Model 4
.  streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  if sample ==1, cluster(sn) d(w) nohr 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 35.262999}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 49.237285}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 49.629864}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 49.641796}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 49.641817}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 49.641817}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:10})} = {res}{ralign 6:78.52}
{txt}Log pseudolikelihood = {res}49.641817{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0114975{col 40}{space 2} .0037362{col 51}{space 1}    3.08{col 60}{space 3}0.002{col 68}{space 4} .0041746{col 81}{space 3} .0188203
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0052596{col 40}{space 2}  .001369{col 51}{space 1}   -3.84{col 60}{space 3}0.000{col 68}{space 4}-.0079427{col 81}{space 3}-.0025765
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0051588{col 40}{space 2} .0134033{col 51}{space 1}   -0.38{col 60}{space 3}0.700{col 68}{space 4}-.0314288{col 81}{space 3} .0211113
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.710859{col 40}{space 2} 1.160581{col 51}{space 1}   -1.47{col 60}{space 3}0.140{col 68}{space 4}-3.985556{col 81}{space 3} .5638378
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0743925{col 40}{space 2} .0218007{col 51}{space 1}   -3.41{col 60}{space 3}0.001{col 68}{space 4}-.1171212{col 81}{space 3}-.0316639
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0074126{col 40}{space 2} .0131364{col 51}{space 1}    0.56{col 60}{space 3}0.573{col 68}{space 4}-.0183342{col 81}{space 3} .0331594
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .9715891{col 40}{space 2} .2782253{col 51}{space 1}    3.49{col 60}{space 3}0.000{col 68}{space 4} .4262776{col 81}{space 3} 1.516901
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.0787981{col 40}{space 2} .1476569{col 51}{space 1}   -0.53{col 60}{space 3}0.594{col 68}{space 4}-.3682004{col 81}{space 3} .2106041
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.166522{col 40}{space 2} .3383473{col 51}{space 1}    3.45{col 60}{space 3}0.001{col 68}{space 4} .5033737{col 81}{space 3} 1.829671
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} .7031905{col 40}{space 2} .4976249{col 51}{space 1}    1.41{col 60}{space 3}0.158{col 68}{space 4}-.2721363{col 81}{space 3} 1.678517
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-37.58896{col 40}{space 2} 5.658993{col 51}{space 1}   -6.64{col 60}{space 3}0.000{col 68}{space 4}-48.68038{col 81}{space 3}-26.49754
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.310941{col 40}{space 2} .1517856{col 51}{space 1}   15.23{col 60}{space 3}0.000{col 68}{space 4} 2.013446{col 81}{space 3} 2.608435
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 10.08391{col 40}{space 2} 1.530592{col 68}{space 4} 7.489083{col 81}{space 3} 13.57779
{txt}                       1/p {c |}{col 28}{res}{space 2} .0991679{col 40}{space 2} .0150523{col 68}{space 4} .0736497{col 81}{space 3} .1335277
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.95896{col 39} 49.64182{col 50}    12{col 58}-75.28363{col 69}-17.97924
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. //Model 5
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, cluster(sn) d(w) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res:  28.18993}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 49.084106}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 49.758278}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 49.764987}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 49.764991}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:12})} = {res}{ralign 6:89.80}
{txt}Log pseudolikelihood = {res}49.764991{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}  .013924{col 40}{space 2} .0038944{col 51}{space 1}    3.58{col 60}{space 3}0.000{col 68}{space 4} .0062912{col 81}{space 3} .0215568
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} -.004383{col 40}{space 2} .0012169{col 51}{space 1}   -3.60{col 60}{space 3}0.000{col 68}{space 4}-.0067681{col 81}{space 3}-.0019978
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}   .01195{col 40}{space 2} .0128584{col 51}{space 1}    0.93{col 60}{space 3}0.353{col 68}{space 4}-.0132521{col 81}{space 3}  .037152
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} -2.05365{col 40}{space 2} 1.736939{col 51}{space 1}   -1.18{col 60}{space 3}0.237{col 68}{space 4}-5.457988{col 81}{space 3} 1.350689
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} -.029981{col 40}{space 2} .0269348{col 51}{space 1}   -1.11{col 60}{space 3}0.266{col 68}{space 4}-.0827722{col 81}{space 3} .0228102
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2}-.0066413{col 40}{space 2} .0155077{col 51}{space 1}   -0.43{col 60}{space 3}0.668{col 68}{space 4}-.0370358{col 81}{space 3} .0237532
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} .6835745{col 40}{space 2} .3205634{col 51}{space 1}    2.13{col 60}{space 3}0.033{col 68}{space 4} .0552818{col 81}{space 3} 1.311867
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0644446{col 40}{space 2} .1846551{col 51}{space 1}    0.35{col 60}{space 3}0.727{col 68}{space 4}-.2974727{col 81}{space 3} .4263619
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-1.283697{col 40}{space 2} .3519322{col 51}{space 1}   -3.65{col 60}{space 3}0.000{col 68}{space 4}-1.973471{col 81}{space 3}-.5939222
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-1.123389{col 40}{space 2} .4012162{col 51}{space 1}   -2.80{col 60}{space 3}0.005{col 68}{space 4}-1.909758{col 81}{space 3}-.3370199
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-1.491564{col 40}{space 2} .4224862{col 51}{space 1}   -3.53{col 60}{space 3}0.000{col 68}{space 4}-2.319622{col 81}{space 3}-.6635065
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.8643724{col 40}{space 2} .4200344{col 51}{space 1}   -2.06{col 60}{space 3}0.040{col 68}{space 4}-1.687625{col 81}{space 3}-.0411201
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-33.34314{col 40}{space 2} 4.908895{col 51}{space 1}   -6.79{col 60}{space 3}0.000{col 68}{space 4} -42.9644{col 81}{space 3}-23.72189
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.302809{col 40}{space 2} .1515258{col 51}{space 1}   15.20{col 60}{space 3}0.000{col 68}{space 4} 2.005824{col 81}{space 3} 2.599794
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 10.00224{col 40}{space 2} 1.515598{col 68}{space 4} 7.432217{col 81}{space 3} 13.46097
{txt}                       1/p {c |}{col 28}{res}{space 2} .0999776{col 40}{space 2} .0151492{col 68}{space 4} .0742889{col 81}{space 3} .1345494
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.95896{col 39} 49.76499{col 50}    14{col 58}-71.52998{col 69}-4.674856
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
. //Model 6
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001        ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, cluster(sn) d(w) nohr  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-76.883661
{txt}Iteration 1:  Log pseudolikelihood = {res} -16.28474
{txt}Iteration 2:  Log pseudolikelihood = {res} 19.099082
{txt}Iteration 3:  Log pseudolikelihood = {res} 24.915716
{txt}Iteration 4:  Log pseudolikelihood = {res} 24.958963
{txt}Iteration 5:  Log pseudolikelihood = {res} 24.958964

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 24.958964}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 45.318014}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 54.014188}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 55.102958}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 55.131957}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 55.132307}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 55.132307}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:15})} = {res}{ralign 6:86.44}
{txt}Log pseudolikelihood = {res}55.132307{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0109657{col 40}{space 2} .0039142{col 51}{space 1}    2.80{col 60}{space 3}0.005{col 68}{space 4}  .003294{col 81}{space 3} .0186374
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0047537{col 40}{space 2} .0013775{col 51}{space 1}   -3.45{col 60}{space 3}0.001{col 68}{space 4}-.0074535{col 81}{space 3}-.0020538
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0004181{col 40}{space 2} .0139724{col 51}{space 1}   -0.03{col 60}{space 3}0.976{col 68}{space 4}-.0278036{col 81}{space 3} .0269673
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.989202{col 40}{space 2} 1.148411{col 51}{space 1}   -1.73{col 60}{space 3}0.083{col 68}{space 4}-4.240046{col 81}{space 3} .2616428
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0390471{col 40}{space 2} .0268074{col 51}{space 1}   -1.46{col 60}{space 3}0.145{col 68}{space 4}-.0915887{col 81}{space 3} .0134944
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2}-.0036289{col 40}{space 2} .0148244{col 51}{space 1}   -0.24{col 60}{space 3}0.807{col 68}{space 4}-.0326843{col 81}{space 3} .0254264
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.448253{col 40}{space 2} .3711774{col 51}{space 1}    3.90{col 60}{space 3}0.000{col 68}{space 4} .7207585{col 81}{space 3} 2.175747
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} -.203216{col 40}{space 2} .1891792{col 51}{space 1}   -1.07{col 60}{space 3}0.283{col 68}{space 4}-.5740005{col 81}{space 3} .1675684
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}-2.155467{col 40}{space 2} 1.921156{col 51}{space 1}   -1.12{col 60}{space 3}0.262{col 68}{space 4}-5.920863{col 81}{space 3} 1.609929
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-1.238967{col 40}{space 2} .3253576{col 51}{space 1}   -3.81{col 60}{space 3}0.000{col 68}{space 4}-1.876656{col 81}{space 3}-.6012777
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-1.441462{col 40}{space 2}  .437548{col 51}{space 1}   -3.29{col 60}{space 3}0.001{col 68}{space 4} -2.29904{col 81}{space 3}-.5838834
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-1.184886{col 40}{space 2} .3996664{col 51}{space 1}   -2.96{col 60}{space 3}0.003{col 68}{space 4}-1.968217{col 81}{space 3}-.4015538
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-1.040852{col 40}{space 2} .4497347{col 51}{space 1}   -2.31{col 60}{space 3}0.021{col 68}{space 4}-1.922316{col 81}{space 3}-.1593883
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.166189{col 40}{space 2} .3831684{col 51}{space 1}    3.04{col 60}{space 3}0.002{col 68}{space 4} .4151924{col 81}{space 3} 1.917185
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} .8665506{col 40}{space 2} .5889057{col 51}{space 1}    1.47{col 60}{space 3}0.141{col 68}{space 4}-.2876834{col 81}{space 3} 2.020785
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-41.71279{col 40}{space 2} 6.213698{col 51}{space 1}   -6.71{col 60}{space 3}0.000{col 68}{space 4}-53.89141{col 81}{space 3}-29.53416
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} 2.388315{col 40}{space 2} .1464975{col 51}{space 1}   16.30{col 60}{space 3}0.000{col 68}{space 4} 2.101186{col 81}{space 3} 2.675445
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 10.89513{col 40}{space 2} 1.596109{col 68}{space 4} 8.175857{col 81}{space 3} 14.51881
{txt}                       1/p {c |}{col 28}{res}{space 2} .0917842{col 40}{space 2} .0134462{col 68}{space 4} .0688761{col 81}{space 3} .1223113
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.95896{col 39} 55.13231{col 50}    17{col 58}-76.26461{col 69} 4.916609
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
.  //LogNormal
.   //Model 1
. streg dist_nat_gap_civil dist_nat_gap_criminal, cluster(sn) d(ln) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-78.466421}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-25.635473}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 12.560701}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  15.11105}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 16.549173}  
Iteration 5:{space 2}Log pseudolikelihood = {res:   16.5542}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 16.554201}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 16.554201}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 24.360122}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 25.320192}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 25.321842}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 25.321842}  
{res}
{txt}Lognormal AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:2})} = {res}{ralign 6:8.65}
{txt}Log pseudolikelihood = {res}25.321842{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0132}

{txt}{ralign 87:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                   _t{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}dist_nat_gap_civil {c |}{col 23}{res}{space 2}-.0031149{col 35}{space 2} .0011187{col 46}{space 1}   -2.78{col 55}{space 3}0.005{col 63}{space 4}-.0053075{col 76}{space 3}-.0009222
{txt}dist_nat_gap_criminal {c |}{col 23}{res}{space 2} .0001956{col 35}{space 2} .0002628{col 46}{space 1}    0.74{col 55}{space 3}0.457{col 63}{space 4}-.0003196{col 76}{space 3} .0007107
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.476821{col 35}{space 2} .0190514{col 46}{space 1}  130.01{col 55}{space 3}0.000{col 63}{space 4} 2.439481{col 76}{space 3} 2.514161
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}/lnsigma {c |}{col 23}{res}{space 2}-1.737693{col 35}{space 2} .1366161{col 46}{space 1}  -12.72{col 55}{space 3}0.000{col 63}{space 4}-2.005455{col 76}{space 3} -1.46993
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma {c |}{col 23}{res}{space 2} .1759258{col 35}{space 2} .0240343{col 63}{space 4}  .134599{col 76}{space 3} .2299415
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}  16.5542{col 39} 25.32184{col 50}     4{col 58}-42.64368{col 69}-23.54222
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 2
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP if sample ==1, cluster(sn) d(ln) hr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-78.466421}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-25.635473}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 12.560701}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  15.11105}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 16.549173}  
Iteration 5:{space 2}Log pseudolikelihood = {res:   16.5542}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 16.554201}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 16.554201}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 20.835391}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 29.126999}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  29.17787}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 29.177976}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 29.177976}  
{res}
{txt}Lognormal AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:6})} = {res}{ralign 6:16.51}
{txt}Log pseudolikelihood = {res}29.177976{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0113}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} -.002519{col 40}{space 2} .0008621{col 51}{space 1}   -2.92{col 60}{space 3}0.003{col 68}{space 4}-.0042086{col 81}{space 3}-.0008294
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}   .00006{col 40}{space 2} .0002249{col 51}{space 1}    0.27{col 60}{space 3}0.790{col 68}{space 4}-.0003808{col 81}{space 3} .0005008
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0018766{col 40}{space 2} .0018595{col 51}{space 1}    1.01{col 60}{space 3}0.313{col 68}{space 4} -.001768{col 81}{space 3} .0055211
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .0390133{col 40}{space 2} .0741478{col 51}{space 1}    0.53{col 60}{space 3}0.599{col 68}{space 4}-.1063137{col 81}{space 3} .1843402
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0054941{col 40}{space 2} .0034007{col 51}{space 1}    1.62{col 60}{space 3}0.106{col 68}{space 4}-.0011712{col 81}{space 3} .0121594
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0007899{col 40}{space 2} .0043467{col 51}{space 1}    0.18{col 60}{space 3}0.856{col 68}{space 4}-.0077295{col 81}{space 3} .0093093
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 2.471756{col 40}{space 2} .0192673{col 51}{space 1}  128.29{col 60}{space 3}0.000{col 68}{space 4} 2.433993{col 81}{space 3} 2.509519
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsigma {c |}{col 28}{res}{space 2}-1.802506{col 40}{space 2} .1322388{col 51}{space 1}  -13.63{col 60}{space 3}0.000{col 68}{space 4} -2.06169{col 81}{space 3}-1.543323
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     sigma {c |}{col 28}{res}{space 2} .1648851{col 40}{space 2} .0218042{col 68}{space 4} .1272388{col 81}{space 3} .2136699
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}  16.5542{col 39} 29.17798{col 50}     8{col 58}-42.35595{col 69}-4.153023
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 3
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> if sample ==1, cluster(sn) d(ln) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-78.466421}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-25.635473}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 12.560701}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  15.11105}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 16.549173}  
Iteration 5:{space 2}Log pseudolikelihood = {res:   16.5542}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 16.554201}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 16.554201}  
Iteration 1:{space 2}Log pseudolikelihood = {res:  31.56799}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 37.338559}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 37.401245}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 37.401445}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 37.401445}  
{res}
{txt}Lognormal AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:9})} = {res}{ralign 6:22.79}
{txt}Log pseudolikelihood = {res}37.401445{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0067}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0028562{col 40}{space 2} .0008856{col 51}{space 1}   -3.23{col 60}{space 3}0.001{col 68}{space 4}-.0045921{col 81}{space 3}-.0011204
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0004144{col 40}{space 2} .0002666{col 51}{space 1}    1.55{col 60}{space 3}0.120{col 68}{space 4}-.0001081{col 81}{space 3} .0009368
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .000966{col 40}{space 2} .0020454{col 51}{space 1}    0.47{col 60}{space 3}0.637{col 68}{space 4} -.003043{col 81}{space 3} .0049749
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .2076847{col 40}{space 2} .1048943{col 51}{space 1}    1.98{col 60}{space 3}0.048{col 68}{space 4} .0020957{col 81}{space 3} .4132737
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0063832{col 40}{space 2} .0035068{col 51}{space 1}    1.82{col 60}{space 3}0.069{col 68}{space 4}  -.00049{col 81}{space 3} .0132564
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0030758{col 40}{space 2} .0036044{col 51}{space 1}    0.85{col 60}{space 3}0.393{col 68}{space 4}-.0039887{col 81}{space 3} .0101403
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} .4022565{col 40}{space 2} .2800583{col 51}{space 1}    1.44{col 60}{space 3}0.151{col 68}{space 4}-.1466477{col 81}{space 3} .9511607
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1704769{col 40}{space 2} .0521358{col 51}{space 1}   -3.27{col 60}{space 3}0.001{col 68}{space 4}-.2726612{col 81}{space 3}-.0682925
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0284873{col 40}{space 2} .0248031{col 51}{space 1}    1.15{col 60}{space 3}0.251{col 68}{space 4}-.0201258{col 81}{space 3} .0771004
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 4.030789{col 40}{space 2} .4272538{col 51}{space 1}    9.43{col 60}{space 3}0.000{col 68}{space 4} 3.193387{col 81}{space 3} 4.868191
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsigma {c |}{col 28}{res}{space 2}-1.874315{col 40}{space 2} .1277192{col 51}{space 1}  -14.68{col 60}{space 3}0.000{col 68}{space 4} -2.12464{col 81}{space 3} -1.62399
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     sigma {c |}{col 28}{res}{space 2}   .15346{col 40}{space 2} .0195998{col 68}{space 4} .1194759{col 81}{space 3} .1971106
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}  16.5542{col 39} 37.40144{col 50}    11{col 58}-52.80289{col 69}-.2738625
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  //Model 4
.  streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  if sample ==1, cluster(sn) d(ln) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-78.466421}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-25.635473}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 12.560701}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  15.11105}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 16.549173}  
Iteration 5:{space 2}Log pseudolikelihood = {res:   16.5542}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 16.554201}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 16.554201}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 36.685846}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 42.080697}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 42.146929}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 42.147147}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 42.147147}  
{res}
{txt}Lognormal AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:10})} = {res}{ralign 6:33.53}
{txt}Log pseudolikelihood = {res}42.147147{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0002}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0021955{col 40}{space 2} .0007792{col 51}{space 1}   -2.82{col 60}{space 3}0.005{col 68}{space 4}-.0037227{col 81}{space 3}-.0006684
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0003777{col 40}{space 2} .0002208{col 51}{space 1}    1.71{col 60}{space 3}0.087{col 68}{space 4}-.0000552{col 81}{space 3} .0008105
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0021952{col 40}{space 2} .0019208{col 51}{space 1}    1.14{col 60}{space 3}0.253{col 68}{space 4}-.0015694{col 81}{space 3} .0059599
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .1639509{col 40}{space 2} .0800537{col 51}{space 1}    2.05{col 60}{space 3}0.041{col 68}{space 4} .0070484{col 81}{space 3} .3208533
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0103425{col 40}{space 2} .0032284{col 51}{space 1}    3.20{col 60}{space 3}0.001{col 68}{space 4} .0040149{col 81}{space 3} .0166701
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0015129{col 40}{space 2}  .002298{col 51}{space 1}    0.66{col 60}{space 3}0.510{col 68}{space 4}-.0029911{col 81}{space 3}  .006017
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1616455{col 40}{space 2} .0414029{col 51}{space 1}   -3.90{col 60}{space 3}0.000{col 68}{space 4}-.2427937{col 81}{space 3}-.0804973
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0313413{col 40}{space 2} .0208517{col 51}{space 1}    1.50{col 60}{space 3}0.133{col 68}{space 4}-.0095274{col 81}{space 3} .0722099
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2}-.1585128{col 40}{space 2} .0482037{col 51}{space 1}   -3.29{col 60}{space 3}0.001{col 68}{space 4}-.2529903{col 81}{space 3}-.0640353
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2}-.0563322{col 40}{space 2} .0601109{col 51}{space 1}   -0.94{col 60}{space 3}0.349{col 68}{space 4}-.1741473{col 81}{space 3}  .061483
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 4.304939{col 40}{space 2} .4197344{col 51}{space 1}   10.26{col 60}{space 3}0.000{col 68}{space 4} 3.482275{col 81}{space 3} 5.127603
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsigma {c |}{col 28}{res}{space 2}-1.951643{col 40}{space 2}  .124177{col 51}{space 1}  -15.72{col 60}{space 3}0.000{col 68}{space 4}-2.195026{col 81}{space 3}-1.708261
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     sigma {c |}{col 28}{res}{space 2} .1420405{col 40}{space 2} .0176382{col 68}{space 4} .1113557{col 81}{space 3} .1811807
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}  16.5542{col 39} 42.14715{col 50}    12{col 58}-60.29429{col 69}-2.989901
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. //Model 5
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, cluster(sn) d(ln) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-78.466421}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-25.635473}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 12.560701}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  15.11105}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 16.549173}  
Iteration 5:{space 2}Log pseudolikelihood = {res:   16.5542}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 16.554201}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 16.554201}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 38.330825}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 43.903908}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 43.984805}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 43.984942}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 43.984942}  
{res}
{txt}Lognormal AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:12})} = {res}{ralign 6:43.67}
{txt}Log pseudolikelihood = {res}43.984942{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0022117{col 40}{space 2} .0007113{col 51}{space 1}   -3.11{col 60}{space 3}0.002{col 68}{space 4}-.0036058{col 81}{space 3}-.0008175
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0002526{col 40}{space 2} .0002352{col 51}{space 1}    1.07{col 60}{space 3}0.283{col 68}{space 4}-.0002084{col 81}{space 3} .0007136
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0001754{col 40}{space 2} .0019408{col 51}{space 1}   -0.09{col 60}{space 3}0.928{col 68}{space 4}-.0039793{col 81}{space 3} .0036284
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .1876557{col 40}{space 2} .0931025{col 51}{space 1}    2.02{col 60}{space 3}0.044{col 68}{space 4} .0051782{col 81}{space 3} .3701332
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0027706{col 40}{space 2} .0034231{col 51}{space 1}    0.81{col 60}{space 3}0.418{col 68}{space 4}-.0039385{col 81}{space 3} .0094797
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0039357{col 40}{space 2} .0032307{col 51}{space 1}    1.22{col 60}{space 3}0.223{col 68}{space 4}-.0023964{col 81}{space 3} .0102677
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1016998{col 40}{space 2}  .035166{col 51}{space 1}   -2.89{col 60}{space 3}0.004{col 68}{space 4}-.1706239{col 81}{space 3}-.0327757
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.0030054{col 40}{space 2} .0291063{col 51}{space 1}   -0.10{col 60}{space 3}0.918{col 68}{space 4}-.0600527{col 81}{space 3} .0540419
{txt}{space 15}region_east {c |}{col 28}{res}{space 2} .2268444{col 40}{space 2} .0664221{col 51}{space 1}    3.42{col 60}{space 3}0.001{col 68}{space 4} .0966594{col 81}{space 3} .3570294
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} .1645718{col 40}{space 2} .0645206{col 51}{space 1}    2.55{col 60}{space 3}0.011{col 68}{space 4} .0381137{col 81}{space 3} .2910299
{txt}{space 15}region_west {c |}{col 28}{res}{space 2} .2447706{col 40}{space 2} .0838442{col 51}{space 1}    2.92{col 60}{space 3}0.004{col 68}{space 4}  .080439{col 81}{space 3} .4091023
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .1865655{col 40}{space 2} .0770287{col 51}{space 1}    2.42{col 60}{space 3}0.015{col 68}{space 4}  .035592{col 81}{space 3}  .337539
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 3.597437{col 40}{space 2} .3338561{col 51}{space 1}   10.78{col 60}{space 3}0.000{col 68}{space 4} 2.943091{col 81}{space 3} 4.251783
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsigma {c |}{col 28}{res}{space 2} -1.98839{col 40}{space 2} .1094535{col 51}{space 1}  -18.17{col 60}{space 3}0.000{col 68}{space 4}-2.202915{col 81}{space 3}-1.773865
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     sigma {c |}{col 28}{res}{space 2} .1369157{col 40}{space 2} .0149859{col 68}{space 4} .1104806{col 81}{space 3} .1696759
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}  16.5542{col 39} 43.98494{col 50}    14{col 58}-59.96988{col 69} 6.885242
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
.  streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001       ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, cluster(sn) d(ln) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-78.466421}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-25.635473}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 12.560701}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  15.11105}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 16.549173}  
Iteration 5:{space 2}Log pseudolikelihood = {res:   16.5542}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 16.554201}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res: 16.554201}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 42.017948}  (backed up)
Iteration 2:{space 2}Log pseudolikelihood = {res: 48.628736}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 48.731964}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 48.732389}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 48.732389}  
{res}
{txt}Lognormal AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:15})} = {res}{ralign 6:53.06}
{txt}Log pseudolikelihood = {res}48.732389{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0018663{col 40}{space 2} .0006446{col 51}{space 1}   -2.90{col 60}{space 3}0.004{col 68}{space 4}-.0031296{col 81}{space 3} -.000603
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0003377{col 40}{space 2} .0002116{col 51}{space 1}    1.60{col 60}{space 3}0.111{col 68}{space 4} -.000077{col 81}{space 3} .0007525
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0013263{col 40}{space 2} .0017619{col 51}{space 1}    0.75{col 60}{space 3}0.452{col 68}{space 4}-.0021269{col 81}{space 3} .0047795
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}  .220243{col 40}{space 2} .0974941{col 51}{space 1}    2.26{col 60}{space 3}0.024{col 68}{space 4}  .029158{col 81}{space 3}  .411328
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0034765{col 40}{space 2} .0034292{col 51}{space 1}    1.01{col 60}{space 3}0.311{col 68}{space 4}-.0032447{col 81}{space 3} .0101977
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0026536{col 40}{space 2} .0021647{col 51}{space 1}    1.23{col 60}{space 3}0.220{col 68}{space 4}-.0015892{col 81}{space 3} .0068964
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1757639{col 40}{space 2} .0531717{col 51}{space 1}   -3.31{col 60}{space 3}0.001{col 68}{space 4}-.2799784{col 81}{space 3}-.0715493
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0155687{col 40}{space 2} .0260221{col 51}{space 1}    0.60{col 60}{space 3}0.550{col 68}{space 4}-.0354337{col 81}{space 3} .0665711
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} .3401121{col 40}{space 2} .3076099{col 51}{space 1}    1.11{col 60}{space 3}0.269{col 68}{space 4}-.2627922{col 81}{space 3} .9430164
{txt}{space 15}region_east {c |}{col 28}{res}{space 2} .1804567{col 40}{space 2} .0580601{col 51}{space 1}    3.11{col 60}{space 3}0.002{col 68}{space 4}  .066661{col 81}{space 3} .2942524
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} .1450386{col 40}{space 2}  .064018{col 51}{space 1}    2.27{col 60}{space 3}0.023{col 68}{space 4} .0195656{col 81}{space 3} .2705116
{txt}{space 15}region_west {c |}{col 28}{res}{space 2} .1939551{col 40}{space 2} .0742987{col 51}{space 1}    2.61{col 60}{space 3}0.009{col 68}{space 4} .0483322{col 81}{space 3} .3395779
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .1899019{col 40}{space 2} .0813969{col 51}{space 1}    2.33{col 60}{space 3}0.020{col 68}{space 4}  .030367{col 81}{space 3} .3494368
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2}-.1257492{col 40}{space 2} .0458749{col 51}{space 1}   -2.74{col 60}{space 3}0.006{col 68}{space 4}-.2156624{col 81}{space 3}-.0358361
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2}-.0725943{col 40}{space 2} .0565229{col 51}{space 1}   -1.28{col 60}{space 3}0.199{col 68}{space 4}-.1833771{col 81}{space 3} .0381886
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 4.187764{col 40}{space 2} .4313668{col 51}{space 1}    9.71{col 60}{space 3}0.000{col 68}{space 4}   3.3423{col 81}{space 3} 5.033227
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lnsigma {c |}{col 28}{res}{space 2}-2.051645{col 40}{space 2} .1019122{col 51}{space 1}  -20.13{col 60}{space 3}0.000{col 68}{space 4}-2.251389{col 81}{space 3}-1.851901
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     sigma {c |}{col 28}{res}{space 2} .1285233{col 40}{space 2} .0130981{col 68}{space 4} .1052529{col 81}{space 3} .1569386
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}  16.5542{col 39} 48.73239{col 50}    17{col 58}-63.46478{col 69} 17.71645
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
.  //LogLogistic
.   //Model 1
. streg dist_nat_gap_civil dist_nat_gap_criminal, cluster(sn) d(ll)  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-106.57456}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-37.742886}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 11.757175}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  18.07287}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 24.262639}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 24.295588}  
Iteration 6:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 7:{space 2}Log pseudolikelihood = {res:  24.29562}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 28.294739}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 29.560314}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 30.051045}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 30.057419}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 30.057419}  
{res}
{txt}Loglogistic AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:2})} = {res}{ralign 6:6.31}
{txt}Log pseudolikelihood = {res}30.057419{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0427}

{txt}{ralign 87:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                   _t{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}dist_nat_gap_civil {c |}{col 23}{res}{space 2}-.0023704{col 35}{space 2} .0011807{col 46}{space 1}   -2.01{col 55}{space 3}0.045{col 63}{space 4}-.0046845{col 76}{space 3}-.0000563
{txt}dist_nat_gap_criminal {c |}{col 23}{res}{space 2} .0002108{col 35}{space 2} .0001784{col 46}{space 1}    1.18{col 55}{space 3}0.237{col 63}{space 4}-.0001389{col 76}{space 3} .0005604
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.490379{col 35}{space 2} .0168108{col 46}{space 1}  148.14{col 55}{space 3}0.000{col 63}{space 4} 2.457431{col 76}{space 3} 2.523328
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}/lngamma {c |}{col 23}{res}{space 2}-2.429066{col 35}{space 2} .1620707{col 46}{space 1}  -14.99{col 55}{space 3}0.000{col 63}{space 4}-2.746719{col 76}{space 3}-2.111414
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                gamma {c |}{col 23}{res}{space 2} .0881191{col 35}{space 2} .0142815{col 63}{space 4} .0641379{col 76}{space 3} .1210667
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.29562{col 39} 30.05742{col 50}     4{col 58}-52.11484{col 69}-33.01337
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 2
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP if sample ==1, cluster(sn) d(ll) 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-106.57456}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-37.742886}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 11.757175}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  18.07287}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 24.262639}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 24.295588}  
Iteration 6:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 7:{space 2}Log pseudolikelihood = {res:  24.29562}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 29.752283}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 31.387227}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 33.814839}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 34.103895}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 34.139911}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 34.140014}  
Iteration 7:{space 2}Log pseudolikelihood = {res: 34.140014}  
{res}
{txt}Loglogistic AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:6})} = {res}{ralign 6:16.81}
{txt}Log pseudolikelihood = {res}34.140014{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0100}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0019873{col 40}{space 2} .0010119{col 51}{space 1}   -1.96{col 60}{space 3}0.050{col 68}{space 4}-.0039706{col 81}{space 3}-3.93e-06
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0001123{col 40}{space 2} .0002243{col 51}{space 1}    0.50{col 60}{space 3}0.617{col 68}{space 4}-.0003273{col 81}{space 3} .0005519
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0013122{col 40}{space 2} .0015357{col 51}{space 1}    0.85{col 60}{space 3}0.393{col 68}{space 4}-.0016977{col 81}{space 3} .0043221
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .0265669{col 40}{space 2} .0677087{col 51}{space 1}    0.39{col 60}{space 3}0.695{col 68}{space 4}-.1061397{col 81}{space 3} .1592736
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0053326{col 40}{space 2} .0029642{col 51}{space 1}    1.80{col 60}{space 3}0.072{col 68}{space 4}-.0004773{col 81}{space 3} .0111424
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0015544{col 40}{space 2} .0046788{col 51}{space 1}    0.33{col 60}{space 3}0.740{col 68}{space 4}-.0076159{col 81}{space 3} .0107248
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 2.479853{col 40}{space 2} .0197495{col 51}{space 1}  125.57{col 60}{space 3}0.000{col 68}{space 4} 2.441145{col 81}{space 3} 2.518561
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lngamma {c |}{col 28}{res}{space 2}-2.495649{col 40}{space 2} .1534256{col 51}{space 1}  -16.27{col 60}{space 3}0.000{col 68}{space 4}-2.796357{col 81}{space 3} -2.19494
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     gamma {c |}{col 28}{res}{space 2}  .082443{col 40}{space 2} .0126489{col 68}{space 4}  .061032{col 81}{space 3} .1113652
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.29562{col 39} 34.14001{col 50}     8{col 58}-52.28003{col 69} -14.0771
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 3
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> if sample ==1, cluster(sn) d(ll)  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-106.57456}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-37.742886}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 11.757175}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  18.07287}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 24.262639}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 24.295588}  
Iteration 6:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 7:{space 2}Log pseudolikelihood = {res:  24.29562}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 36.430755}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 39.946908}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 40.068089}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 40.070661}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 40.070675}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 40.070675}  
{res}
{txt}Loglogistic AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:9})} = {res}{ralign 6:25.52}
{txt}Log pseudolikelihood = {res}40.070675{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0024}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0020731{col 40}{space 2} .0008978{col 51}{space 1}   -2.31{col 60}{space 3}0.021{col 68}{space 4}-.0038328{col 81}{space 3}-.0003134
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0004176{col 40}{space 2} .0003298{col 51}{space 1}    1.27{col 60}{space 3}0.205{col 68}{space 4}-.0002287{col 81}{space 3}  .001064
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0009272{col 40}{space 2} .0021453{col 51}{space 1}    0.43{col 60}{space 3}0.666{col 68}{space 4}-.0032776{col 81}{space 3}  .005132
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .1676767{col 40}{space 2} .1300888{col 51}{space 1}    1.29{col 60}{space 3}0.197{col 68}{space 4}-.0872926{col 81}{space 3}  .422646
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0056472{col 40}{space 2} .0035798{col 51}{space 1}    1.58{col 60}{space 3}0.115{col 68}{space 4}-.0013691{col 81}{space 3} .0126636
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0021143{col 40}{space 2} .0078244{col 51}{space 1}    0.27{col 60}{space 3}0.787{col 68}{space 4}-.0132212{col 81}{space 3} .0174499
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} .3345299{col 40}{space 2} .3115573{col 51}{space 1}    1.07{col 60}{space 3}0.283{col 68}{space 4}-.2761111{col 81}{space 3} .9451709
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1389409{col 40}{space 2} .0588397{col 51}{space 1}   -2.36{col 60}{space 3}0.018{col 68}{space 4}-.2542647{col 81}{space 3}-.0236171
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0245647{col 40}{space 2} .0355921{col 51}{space 1}    0.69{col 60}{space 3}0.490{col 68}{space 4}-.0451945{col 81}{space 3}  .094324
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 3.734881{col 40}{space 2} .5764306{col 51}{space 1}    6.48{col 60}{space 3}0.000{col 68}{space 4} 2.605098{col 81}{space 3} 4.864664
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lngamma {c |}{col 28}{res}{space 2}-2.543115{col 40}{space 2} .1557658{col 51}{space 1}  -16.33{col 60}{space 3}0.000{col 68}{space 4} -2.84841{col 81}{space 3} -2.23782
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     gamma {c |}{col 28}{res}{space 2} .0786211{col 40}{space 2} .0122465{col 68}{space 4} .0579364{col 81}{space 3} .1066909
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.29562{col 39} 40.07067{col 50}    11{col 58}-58.14135{col 69}-5.612323
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  //Model 4
.  streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  if sample ==1, cluster(sn) d(ll)  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-106.57456}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-37.742886}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 11.757175}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  18.07287}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 24.262639}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 24.295588}  
Iteration 6:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 7:{space 2}Log pseudolikelihood = {res:  24.29562}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 39.695282}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 44.175513}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 45.183073}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 45.214424}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 45.214459}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 45.214459}  
{res}
{txt}Loglogistic AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:10})} = {res}{ralign 6:44.62}
{txt}Log pseudolikelihood = {res}45.214459{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0014852{col 40}{space 2} .0007228{col 51}{space 1}   -2.05{col 60}{space 3}0.040{col 68}{space 4}-.0029018{col 81}{space 3}-.0000686
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0003999{col 40}{space 2} .0001624{col 51}{space 1}    2.46{col 60}{space 3}0.014{col 68}{space 4} .0000816{col 81}{space 3} .0007181
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0016299{col 40}{space 2} .0015708{col 51}{space 1}    1.04{col 60}{space 3}0.299{col 68}{space 4}-.0014487{col 81}{space 3} .0047086
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .1377993{col 40}{space 2} .0893051{col 51}{space 1}    1.54{col 60}{space 3}0.123{col 68}{space 4}-.0372354{col 81}{space 3} .3128341
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0092162{col 40}{space 2} .0029307{col 51}{space 1}    3.14{col 60}{space 3}0.002{col 68}{space 4} .0034721{col 81}{space 3} .0149603
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0004289{col 40}{space 2} .0016415{col 51}{space 1}    0.26{col 60}{space 3}0.794{col 68}{space 4}-.0027884{col 81}{space 3} .0036462
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1461614{col 40}{space 2} .0393173{col 51}{space 1}   -3.72{col 60}{space 3}0.000{col 68}{space 4}-.2232219{col 81}{space 3}-.0691008
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}  .028913{col 40}{space 2} .0203804{col 51}{space 1}    1.42{col 60}{space 3}0.156{col 68}{space 4}-.0110318{col 81}{space 3} .0688579
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2}-.1470066{col 40}{space 2} .0428391{col 51}{space 1}   -3.43{col 60}{space 3}0.001{col 68}{space 4}-.2309697{col 81}{space 3}-.0630434
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2}-.0786417{col 40}{space 2} .0543184{col 51}{space 1}   -1.45{col 60}{space 3}0.148{col 68}{space 4}-.1851038{col 81}{space 3} .0278205
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}  4.13974{col 40}{space 2} .3775225{col 51}{space 1}   10.97{col 60}{space 3}0.000{col 68}{space 4} 3.399809{col 81}{space 3}  4.87967
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lngamma {c |}{col 28}{res}{space 2}-2.634099{col 40}{space 2} .1616886{col 51}{space 1}  -16.29{col 60}{space 3}0.000{col 68}{space 4}-2.951003{col 81}{space 3}-2.317195
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     gamma {c |}{col 28}{res}{space 2} .0717836{col 40}{space 2} .0116066{col 68}{space 4} .0522873{col 81}{space 3} .0985496
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.29562{col 39} 45.21446{col 50}    12{col 58}-66.42892{col 69}-9.124526
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. //Model 5
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, cluster(sn) d(ll)  

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-106.57456}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-37.742886}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 11.757175}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  18.07287}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 24.262639}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 24.295588}  
Iteration 6:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 7:{space 2}Log pseudolikelihood = {res:  24.29562}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 1:{space 2}Log pseudolikelihood = {res: 41.530819}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 44.902602}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 45.693563}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 45.708647}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 45.708676}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 45.708676}  
{res}
{txt}Loglogistic AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:12})} = {res}{ralign 6:54.43}
{txt}Log pseudolikelihood = {res}45.708676{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0016411{col 40}{space 2} .0007393{col 51}{space 1}   -2.22{col 60}{space 3}0.026{col 68}{space 4}-.0030901{col 81}{space 3} -.000192
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0002699{col 40}{space 2} .0002407{col 51}{space 1}    1.12{col 60}{space 3}0.262{col 68}{space 4}-.0002019{col 81}{space 3} .0007417
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0004322{col 40}{space 2} .0017913{col 51}{space 1}    0.24{col 60}{space 3}0.809{col 68}{space 4}-.0030787{col 81}{space 3} .0039431
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .1281717{col 40}{space 2} .0947433{col 51}{space 1}    1.35{col 60}{space 3}0.176{col 68}{space 4}-.0575217{col 81}{space 3} .3138652
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0027669{col 40}{space 2} .0035557{col 51}{space 1}    0.78{col 60}{space 3}0.436{col 68}{space 4}-.0042021{col 81}{space 3} .0097359
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0030332{col 40}{space 2} .0058819{col 51}{space 1}    0.52{col 60}{space 3}0.606{col 68}{space 4} -.008495{col 81}{space 3} .0145614
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.0853131{col 40}{space 2} .0326545{col 51}{space 1}   -2.61{col 60}{space 3}0.009{col 68}{space 4}-.1493146{col 81}{space 3}-.0213115
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.0028693{col 40}{space 2} .0363197{col 51}{space 1}   -0.08{col 60}{space 3}0.937{col 68}{space 4}-.0740546{col 81}{space 3} .0683159
{txt}{space 15}region_east {c |}{col 28}{res}{space 2} .1959825{col 40}{space 2} .0736992{col 51}{space 1}    2.66{col 60}{space 3}0.008{col 68}{space 4} .0515347{col 81}{space 3} .3404303
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} .1627751{col 40}{space 2}  .066826{col 51}{space 1}    2.44{col 60}{space 3}0.015{col 68}{space 4} .0317985{col 81}{space 3} .2937517
{txt}{space 15}region_west {c |}{col 28}{res}{space 2} .2096823{col 40}{space 2}  .099913{col 51}{space 1}    2.10{col 60}{space 3}0.036{col 68}{space 4} .0138564{col 81}{space 3} .4055081
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .1597733{col 40}{space 2}  .088159{col 51}{space 1}    1.81{col 60}{space 3}0.070{col 68}{space 4}-.0130152{col 81}{space 3} .3325617
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}   3.4172{col 40}{space 2} .3706781{col 51}{space 1}    9.22{col 60}{space 3}0.000{col 68}{space 4} 2.690684{col 81}{space 3} 4.143716
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lngamma {c |}{col 28}{res}{space 2}-2.637354{col 40}{space 2} .1523212{col 51}{space 1}  -17.31{col 60}{space 3}0.000{col 68}{space 4}-2.935898{col 81}{space 3} -2.33881
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     gamma {c |}{col 28}{res}{space 2} .0715504{col 40}{space 2} .0108986{col 68}{space 4}  .053083{col 81}{space 3} .0964424
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.29562{col 39} 45.70868{col 50}    14{col 58}-63.41735{col 69} 3.437773
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
.  //Model 6
.  streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001       ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, cluster(sn) d(ll)   

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Fitting constant-only model:
{res}{txt}{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-106.57456}  (not concave)
Iteration 1:{space 2}Log pseudolikelihood = {res:-37.742886}  
Iteration 2:{space 2}Log pseudolikelihood = {res: 11.757175}  
Iteration 3:{space 2}Log pseudolikelihood = {res:  18.07287}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 24.262639}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 24.295588}  
Iteration 6:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 7:{space 2}Log pseudolikelihood = {res:  24.29562}  
{res}
{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:  24.29562}  
Iteration 1:{space 2}Log pseudolikelihood = {res:  25.51156}  (not concave)
Iteration 2:{space 2}Log pseudolikelihood = {res: 30.349809}  
Iteration 3:{space 2}Log pseudolikelihood = {res: 40.493335}  
Iteration 4:{space 2}Log pseudolikelihood = {res: 47.499968}  
Iteration 5:{space 2}Log pseudolikelihood = {res: 50.016386}  
Iteration 6:{space 2}Log pseudolikelihood = {res: 50.137614}  
Iteration 7:{space 2}Log pseudolikelihood = {res: 50.138044}  
Iteration 8:{space 2}Log pseudolikelihood = {res: 50.138044}  
{res}
{txt}Loglogistic AFT regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:15})} = {res}{ralign 6:79.43}
{txt}Log pseudolikelihood = {res}50.138044{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2}-.0014251{col 40}{space 2} .0007874{col 51}{space 1}   -1.81{col 60}{space 3}0.070{col 68}{space 4}-.0029684{col 81}{space 3} .0001183
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2} .0003385{col 40}{space 2} .0001631{col 51}{space 1}    2.08{col 60}{space 3}0.038{col 68}{space 4} .0000188{col 81}{space 3} .0006582
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0014321{col 40}{space 2} .0016625{col 51}{space 1}    0.86{col 60}{space 3}0.389{col 68}{space 4}-.0018264{col 81}{space 3} .0046905
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2} .1639549{col 40}{space 2} .1137108{col 51}{space 1}    1.44{col 60}{space 3}0.149{col 68}{space 4}-.0589142{col 81}{space 3} .3868241
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} .0039807{col 40}{space 2} .0038126{col 51}{space 1}    1.04{col 60}{space 3}0.296{col 68}{space 4}-.0034918{col 81}{space 3} .0114532
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0013997{col 40}{space 2} .0017141{col 51}{space 1}    0.82{col 60}{space 3}0.414{col 68}{space 4}-.0019598{col 81}{space 3} .0047593
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2}-.1482374{col 40}{space 2} .0518902{col 51}{space 1}   -2.86{col 60}{space 3}0.004{col 68}{space 4}-.2499404{col 81}{space 3}-.0465345
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} .0122029{col 40}{space 2}  .028389{col 51}{space 1}    0.43{col 60}{space 3}0.667{col 68}{space 4}-.0434385{col 81}{space 3} .0678442
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}  .239624{col 40}{space 2}  .298857{col 51}{space 1}    0.80{col 60}{space 3}0.423{col 68}{space 4} -.346125{col 81}{space 3}  .825373
{txt}{space 15}region_east {c |}{col 28}{res}{space 2} .1503049{col 40}{space 2} .0674946{col 51}{space 1}    2.23{col 60}{space 3}0.026{col 68}{space 4} .0180179{col 81}{space 3}  .282592
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2} .1247165{col 40}{space 2} .0761515{col 51}{space 1}    1.64{col 60}{space 3}0.101{col 68}{space 4}-.0245377{col 81}{space 3} .2739706
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}  .159445{col 40}{space 2} .0937914{col 51}{space 1}    1.70{col 60}{space 3}0.089{col 68}{space 4}-.0243827{col 81}{space 3} .3432726
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .1463693{col 40}{space 2} .0987258{col 51}{space 1}    1.48{col 60}{space 3}0.138{col 68}{space 4}-.0471297{col 81}{space 3} .3398683
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2}-.1123858{col 40}{space 2} .0484989{col 51}{space 1}   -2.32{col 60}{space 3}0.020{col 68}{space 4}-.2074419{col 81}{space 3}-.0173296
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2}-.0712873{col 40}{space 2} .0620821{col 51}{space 1}   -1.15{col 60}{space 3}0.251{col 68}{space 4} -.192966{col 81}{space 3} .0503913
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 3.980034{col 40}{space 2} .4312743{col 51}{space 1}    9.23{col 60}{space 3}0.000{col 68}{space 4} 3.134752{col 81}{space 3} 4.825316
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 18}/lngamma {c |}{col 28}{res}{space 2}-2.695937{col 40}{space 2} .1585413{col 51}{space 1}  -17.00{col 60}{space 3}0.000{col 68}{space 4}-3.006672{col 81}{space 3}-2.385202
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                     gamma {c |}{col 28}{res}{space 2} .0674791{col 40}{space 2} .0106982{col 68}{space 4}  .049456{col 81}{space 3} .0920704
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28} 24.29562{col 39} 50.13804{col 50}    17{col 58}-66.27609{col 69} 14.90514
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
.  ///Expnential 
>  
.   //Model 1
. streg dist_nat_gap_civil dist_nat_gap_criminal, cluster(sn) d(e) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-76.883661}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-71.651941}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-63.885642}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-63.519464}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-63.518315}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-63.518315}  
{res}
{txt}Exponential PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:2})} = {res}{ralign 6:48.09}
{txt}Log pseudolikelihood = {res}-63.518315{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 87:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}                   _t{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}dist_nat_gap_civil {c |}{col 23}{res}{space 2} .0195798{col 35}{space 2} .0036625{col 46}{space 1}    5.35{col 55}{space 3}0.000{col 63}{space 4} .0124015{col 76}{space 3}  .026758
{txt}dist_nat_gap_criminal {c |}{col 23}{res}{space 2}-.0030244{col 35}{space 2} .0007363{col 46}{space 1}   -4.11{col 55}{space 3}0.000{col 63}{space 4}-.0044674{col 76}{space 3}-.0015813
{txt}{space 16}_cons {c |}{col 23}{res}{space 2}-2.682079{col 35}{space 2} .0635989{col 46}{space 1}  -42.17{col 55}{space 3}0.000{col 63}{space 4}-2.806731{col 76}{space 3}-2.557428
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-76.88366{col 39}-63.51832{col 50}     3{col 58} 133.0366{col 69} 147.3627
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 2
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP if sample ==1, cluster(sn) d(e) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-76.883661}  
Iteration 1:{space 2}Log pseudolikelihood = {res: -71.41348}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-63.467524}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-62.953282}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-62.952608}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-62.952608}  
{res}
{txt}Exponential PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:6})} = {res}{ralign 6:64.30}
{txt}Log pseudolikelihood = {res}-62.952608{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0201034{col 40}{space 2} .0037759{col 51}{space 1}    5.32{col 60}{space 3}0.000{col 68}{space 4} .0127029{col 81}{space 3} .0275039
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0026596{col 40}{space 2} .0007458{col 51}{space 1}   -3.57{col 60}{space 3}0.000{col 68}{space 4}-.0041215{col 81}{space 3}-.0011978
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0005092{col 40}{space 2} .0095684{col 51}{space 1}   -0.05{col 60}{space 3}0.958{col 68}{space 4}-.0192629{col 81}{space 3} .0182445
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.2010042{col 40}{space 2} .4048885{col 51}{space 1}   -0.50{col 60}{space 3}0.620{col 68}{space 4}-.9945711{col 81}{space 3} .5925628
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0014995{col 40}{space 2} .0142527{col 51}{space 1}   -0.11{col 60}{space 3}0.916{col 68}{space 4}-.0294343{col 81}{space 3} .0264353
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0114464{col 40}{space 2} .0098903{col 51}{space 1}    1.16{col 60}{space 3}0.247{col 68}{space 4}-.0079382{col 81}{space 3}  .030831
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-2.688644{col 40}{space 2} .0664479{col 51}{space 1}  -40.46{col 60}{space 3}0.000{col 68}{space 4}-2.818879{col 81}{space 3}-2.558408
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-76.88366{col 39}-62.95261{col 50}     7{col 58} 139.9052{col 69} 173.3328
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 3
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP cast_eth_fract ln_pop ln_abs_total2001 ///
> if sample ==1, cluster(sn) d(e) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-76.883661}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-65.254644}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-52.541471}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-52.007257}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-52.006369}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-52.006369}  
{res}
{txt}Exponential PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:9})} = {res}{ralign 6:73.61}
{txt}Log pseudolikelihood = {res}-52.006369{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0261849{col 40}{space 2} .0044745{col 51}{space 1}    5.85{col 60}{space 3}0.000{col 68}{space 4} .0174149{col 81}{space 3} .0349548
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0040148{col 40}{space 2} .0013282{col 51}{space 1}   -3.02{col 60}{space 3}0.003{col 68}{space 4}-.0066181{col 81}{space 3}-.0014115
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}  .012866{col 40}{space 2} .0098773{col 51}{space 1}    1.30{col 60}{space 3}0.193{col 68}{space 4} -.006493{col 81}{space 3} .0322251
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.615027{col 40}{space 2} .8498597{col 51}{space 1}   -1.90{col 60}{space 3}0.057{col 68}{space 4}-3.280721{col 81}{space 3} .0506679
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0186588{col 40}{space 2} .0174013{col 51}{space 1}   -1.07{col 60}{space 3}0.284{col 68}{space 4}-.0527647{col 81}{space 3}  .015447
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0136927{col 40}{space 2} .0128579{col 51}{space 1}    1.06{col 60}{space 3}0.287{col 68}{space 4}-.0115084{col 81}{space 3} .0388939
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2}-3.333501{col 40}{space 2} 1.159571{col 51}{space 1}   -2.87{col 60}{space 3}0.004{col 68}{space 4}-5.606219{col 81}{space 3}-1.060784
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.263809{col 40}{space 2} .2262281{col 51}{space 1}    5.59{col 60}{space 3}0.000{col 68}{space 4}   .82041{col 81}{space 3} 1.707208
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2} -.246571{col 40}{space 2}  .097291{col 51}{space 1}   -2.53{col 60}{space 3}0.011{col 68}{space 4}-.4372579{col 81}{space 3}-.0558841
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-13.63004{col 40}{space 2} 1.797465{col 51}{space 1}   -7.58{col 60}{space 3}0.000{col 68}{space 4}-17.15301{col 81}{space 3}-10.10708
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-76.88366{col 39}-52.00637{col 50}    10{col 58} 124.0127{col 69} 171.7664
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 4
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
> hilli_region mountain_region  if sample ==1, cluster(sn) d(e) nohr 

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-76.883661}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-64.069545}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-51.369381}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-50.932077}  
Iteration 4:{space 2}Log pseudolikelihood = {res: -50.93133}  
Iteration 5:{space 2}Log pseudolikelihood = {res: -50.93133}  
{res}
{txt}Exponential PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:10})} = {res}{ralign 6:83.46}
{txt}Log pseudolikelihood = {res}-50.93133{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0248807{col 40}{space 2} .0044107{col 51}{space 1}    5.64{col 60}{space 3}0.000{col 68}{space 4} .0162359{col 81}{space 3} .0335255
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0040351{col 40}{space 2} .0013313{col 51}{space 1}   -3.03{col 60}{space 3}0.002{col 68}{space 4}-.0066445{col 81}{space 3}-.0014257
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0033992{col 40}{space 2} .0109877{col 51}{space 1}    0.31{col 60}{space 3}0.757{col 68}{space 4}-.0181363{col 81}{space 3} .0249347
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.141102{col 40}{space 2}  .579055{col 51}{space 1}   -1.97{col 60}{space 3}0.049{col 68}{space 4}-2.276028{col 81}{space 3}-.0061746
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0406358{col 40}{space 2} .0155543{col 51}{space 1}   -2.61{col 60}{space 3}0.009{col 68}{space 4}-.0711216{col 81}{space 3}  -.01015
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0259251{col 40}{space 2} .0147981{col 51}{space 1}    1.75{col 60}{space 3}0.080{col 68}{space 4}-.0030787{col 81}{space 3} .0549288
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.477017{col 40}{space 2} .3237334{col 51}{space 1}    4.56{col 60}{space 3}0.000{col 68}{space 4} .8425111{col 81}{space 3} 2.111523
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.1959321{col 40}{space 2} .0901625{col 51}{space 1}   -2.17{col 60}{space 3}0.030{col 68}{space 4}-.3726473{col 81}{space 3}-.0192168
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} .9323922{col 40}{space 2} .3243061{col 51}{space 1}    2.88{col 60}{space 3}0.004{col 68}{space 4} .2967639{col 81}{space 3} 1.568021
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.238325{col 40}{space 2} .4955669{col 51}{space 1}    2.50{col 60}{space 3}0.012{col 68}{space 4} .2670317{col 81}{space 3} 2.209618
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} -20.0764{col 40}{space 2} 3.973887{col 51}{space 1}   -5.05{col 60}{space 3}0.000{col 68}{space 4}-27.86508{col 81}{space 3}-12.28773
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-76.88366{col 39}-50.93133{col 50}    11{col 58} 123.8627{col 69} 176.3917
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. 
. //Model 5
. streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001 ///
>  region_east region_mid region_west region_farwest  if sample ==1, cluster(sn) d(e) nohr

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-76.883661}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-66.263112}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-53.592414}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-52.856095}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-52.855115}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-52.855115}  
{res}
{txt}Exponential PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:12})} = {res}{ralign 6:102.86}
{txt}Log pseudolikelihood = {res}-52.855115{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0266294{col 40}{space 2} .0047449{col 51}{space 1}    5.61{col 60}{space 3}0.000{col 68}{space 4} .0173297{col 81}{space 3} .0359292
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0034781{col 40}{space 2} .0012492{col 51}{space 1}   -2.78{col 60}{space 3}0.005{col 68}{space 4}-.0059265{col 81}{space 3}-.0010297
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .0175274{col 40}{space 2} .0110444{col 51}{space 1}    1.59{col 60}{space 3}0.113{col 68}{space 4}-.0041193{col 81}{space 3} .0391741
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.218847{col 40}{space 2} .7860858{col 51}{space 1}   -1.55{col 60}{space 3}0.121{col 68}{space 4}-2.759547{col 81}{space 3} .3218531
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} -.021039{col 40}{space 2} .0194919{col 51}{space 1}   -1.08{col 60}{space 3}0.280{col 68}{space 4}-.0592425{col 81}{space 3} .0171645
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0060776{col 40}{space 2} .0116837{col 51}{space 1}    0.52{col 60}{space 3}0.603{col 68}{space 4} -.016822{col 81}{space 3} .0289772
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.091354{col 40}{space 2} .1586182{col 51}{space 1}    6.88{col 60}{space 3}0.000{col 68}{space 4} .7804676{col 81}{space 3}  1.40224
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.2887281{col 40}{space 2}  .079799{col 51}{space 1}   -3.62{col 60}{space 3}0.000{col 68}{space 4}-.4451313{col 81}{space 3}-.1323249
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.4281456{col 40}{space 2} .2203625{col 51}{space 1}   -1.94{col 60}{space 3}0.052{col 68}{space 4}-.8600482{col 81}{space 3} .0037571
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.4557509{col 40}{space 2} .2460325{col 51}{space 1}   -1.85{col 60}{space 3}0.064{col 68}{space 4}-.9379657{col 81}{space 3} .0264639
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.1835928{col 40}{space 2} .2241569{col 51}{space 1}   -0.82{col 60}{space 3}0.413{col 68}{space 4}-.6229323{col 81}{space 3} .2557468
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2} .0202224{col 40}{space 2} .2019039{col 51}{space 1}    0.10{col 60}{space 3}0.920{col 68}{space 4} -.375502{col 81}{space 3} .4159468
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-13.54898{col 40}{space 2} 1.710614{col 51}{space 1}   -7.92{col 60}{space 3}0.000{col 68}{space 4}-16.90172{col 81}{space 3}-10.19624
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.  estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       876{col 28}-76.88366{col 39}-52.85512{col 50}    13{col 58} 131.7102{col 69}   193.79
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}.  
.   //Model 6
.  streg dist_nat_gap_civil dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP  percent_votes1991_1999_GAP  ln_pop ln_abs_total2001       ///
> cast_eth_fract region_east region_mid region_west region_farwest hilli_region mountain_region if sample ==1, cluster(sn) d(e) nohr   

{col 9}{txt}Failure {bf:_d}: {res}year_25death
{col 3}{txt}Analysis time {bf:_t}: {res}time
{col 8}{txt}ID variable: {res}sn

{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-76.883661}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-63.366125}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-49.793662}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-49.016165}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-49.014904}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-49.014904}  
{res}
{txt}Exponential PH regression

No. of subjects = {res}{ralign 3:75}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:876}
{txt}No. of failures = {res}{ralign 3:71}
{txt}Time at risk    = {res}{ralign 3:876}
{col 57}{txt}{lalign 13:Wald chi2({res:15})} = {res}{ralign 6:95.83}
{txt}Log pseudolikelihood = {res}-49.014904{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:0.0000}

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sn})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}dist_nat_gap_civil {c |}{col 28}{res}{space 2} .0254398{col 40}{space 2} .0045224{col 51}{space 1}    5.63{col 60}{space 3}0.000{col 68}{space 4} .0165761{col 81}{space 3} .0343034
{txt}{space 5}dist_nat_gap_criminal {c |}{col 28}{res}{space 2}-.0040149{col 40}{space 2} .0012407{col 51}{space 1}   -3.24{col 60}{space 3}0.001{col 68}{space 4}-.0064466{col 81}{space 3}-.0015831
{txt}{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0003197{col 40}{space 2}   .01381{col 51}{space 1}   -0.02{col 60}{space 3}0.982{col 68}{space 4}-.0273867{col 81}{space 3} .0267474
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.284576{col 40}{space 2}  .671709{col 51}{space 1}   -1.91{col 60}{space 3}0.056{col 68}{space 4}-2.601102{col 81}{space 3} .0319493
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}-.0075153{col 40}{space 2} .0210193{col 51}{space 1}   -0.36{col 60}{space 3}0.721{col 68}{space 4}-.0487125{col 81}{space 3} .0336818
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} .0297544{col 40}{space 2}  .016197{col 51}{space 1}    1.84{col 60}{space 3}0.066{col 68}{space 4}-.0019912{col 81}{space 3}    .0615
{txt}{space 20}ln_pop {c |}{col 28}{res}{space 2} 1.911118{col 40}{space 2} .4484099{col 51}{space 1}    4.26{col 60}{space 3}0.000{col 68}{space 4} 1.032251{col 81}{space 3} 2.789986
{txt}{space 10}ln_abs_total2001 {c |}{col 28}{res}{space 2}-.3263784{col 40}{space 2} .1059973{col 51}{space 1}   -3.08{col 60}{space 3}0.002{col 68}{space 4}-.5341292{col 81}{space 3}-.1186276
{txt}{space 12}cast_eth_fract {c |}{col 28}{res}{space 2} -2.25076{col 40}{space 2} 1.973858{col 51}{space 1}   -1.14{col 60}{space 3}0.254{col 68}{space 4}-6.119451{col 81}{space 3} 1.617932
{txt}{space 15}region_east {c |}{col 28}{res}{space 2}-.4163499{col 40}{space 2} .3663236{col 51}{space 1}   -1.14{col 60}{space 3}0.256{col 68}{space 4}-1.134331{col 81}{space 3} .3016312
{txt}{space 16}region_mid {c |}{col 28}{res}{space 2}-.6854633{col 40}{space 2} .4787685{col 51}{space 1}   -1.43{col 60}{space 3}0.152{col 68}{space 4}-1.623832{col 81}{space 3} .2529057
{txt}{space 15}region_west {c |}{col 28}{res}{space 2}-.1483476{col 40}{space 2} .3083612{col 51}{space 1}   -0.48{col 60}{space 3}0.630{col 68}{space 4}-.7527243{col 81}{space 3} .4560292
{txt}{space 12}region_farwest {c |}{col 28}{res}{space 2}-.0519749{col 40}{space 2} .2881689{col 51}{space 1}   -0.18{col 60}{space 3}0.857{col 68}{space 4}-.6167755{col 81}{space 3} .5128258
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} 1.034276{col 40}{space 2} .5149566{col 51}{space 1}    2.01{col 60}{space 3}0.045{col 68}{space 4} .0249796{col 81}{space 3} 2.043572
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2} 1.429684{col 40}{space 2} .7994045{col 51}{space 1}    1.79{col 60}{space 3}0.074{col 68}{space 4}-.1371196{col 81}{space 3} 2.996488
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} -22.3261{col 40}{space 2} 6.207458{col 51}{space 1}   -3.60{col 60}{space 3}0.000{col 68}{space 4} -34.4925{col 81}{space 3}-10.15971
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.  
.  
.  //Endogeneity Test
.  
. xtreg dist_nat_gap_civil litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP percent_votes1991_1999_GAP hilli_region mountain_region if year<2007 & sample==1, vce(robust)
{txt}(2 missing values generated)
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}       876
{txt}Group variable: {res}sno                             {txt}Number of groups  = {res}        75

{txt}R-squared:                                      Obs per group:
     Within  = {res}0.0000                                         {txt}min = {res}         6
{txt}     Between = {res}0.2361                                         {txt}avg = {res}      11.7
{txt}     Overall = {res}0.0144                                         {txt}max = {res}        15

                                                {txt}Wald chi2({res}6{txt})      =  {res}     8.06
{txt}corr(u_i, X) = {res}0{txt} (assumed)                      Prob > chi2       =     {res}0.2336

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}        dist_nat_gap_civil{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2} .3300569{col 40}{space 2} .2603571{col 51}{space 1}    1.27{col 60}{space 3}0.205{col 68}{space 4}-.1802336{col 81}{space 3} .8403475
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-.3300539{col 40}{space 2} 4.106046{col 51}{space 1}   -0.08{col 60}{space 3}0.936{col 68}{space 4}-8.377756{col 81}{space 3} 7.717649
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2} -.664566{col 40}{space 2} .6730663{col 51}{space 1}   -0.99{col 60}{space 3}0.323{col 68}{space 4}-1.983752{col 81}{space 3} .6546197
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2}-.3352169{col 40}{space 2} .2697589{col 51}{space 1}   -1.24{col 60}{space 3}0.214{col 68}{space 4}-.8639346{col 81}{space 3} .1935009
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2}-4.239326{col 40}{space 2} 4.056535{col 51}{space 1}   -1.05{col 60}{space 3}0.296{col 68}{space 4}-12.18999{col 81}{space 3} 3.711336
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2}-29.42106{col 40}{space 2} 15.11035{col 51}{space 1}   -1.95{col 60}{space 3}0.052{col 68}{space 4}-59.03681{col 81}{space 3} .1946901
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} 1.221081{col 40}{space 2} 2.769114{col 51}{space 1}    0.44{col 60}{space 3}0.659{col 68}{space 4}-4.206282{col 81}{space 3} 6.648445
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |} {res}         0
                   {txt}sigma_e {c |} {res} 88.727814
                       {txt}rho {c |} {res}         0{txt}   (fraction of variance due to u_i)
{hline 27}{c BT}{hline 64}

{com}. vif, uncen

{txt}    Variable {c |}       VIF       1/VIF  
{hline 13}{c +}{hline 22}
litrate_19~P {c |} {res}     1.66    0.602030
{txt}lifeexp_19~P {c |} {res}     1.58    0.630986
{txt}road_densi~P {c |} {res}     1.43    0.697000
{txt}mountain_r~n {c |} {res}     1.15    0.870161
{txt}percent_vo~P {c |} {res}     1.15    0.873170
{txt}hilli_region {c |} {res}     1.12    0.896766
{txt}{hline 13}{c +}{hline 22}
    Mean VIF {c |} {res}     1.35
{txt}
{com}. 
. xtreg dist_nat_gap_criminal litrate_1991_2001_GAP road_density_GAP lifeexp_1990_2011_GAP percent_votes1991_1999_GAP hilli_region mountain_region if year<2007 & sample==1, vce(robust)
{txt}(2 missing values generated)
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}       876
{txt}Group variable: {res}sno                             {txt}Number of groups  = {res}        75

{txt}R-squared:                                      Obs per group:
     Within  = {res}0.0014                                         {txt}min = {res}         6
{txt}     Between = {res}0.0728                                         {txt}avg = {res}      11.7
{txt}     Overall = {res}0.0025                                         {txt}max = {res}        15

                                                {txt}Wald chi2({res}6{txt})      =  {res}     4.40
{txt}corr(u_i, X) = {res}0{txt} (assumed)                      Prob > chi2       =     {res}0.6228

{txt}{ralign 92:(Std. err. adjusted for {res:75} clusters in {res:sno})}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}     dist_nat_gap_criminal{col 28}{c |} Coefficient{col 40}  std. err.{col 52}      z{col 60}   P>|z|{col 68}     [95% con{col 81}f. interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}litrate_1991_2001_GAP {c |}{col 28}{res}{space 2}-.0567914{col 40}{space 2} .1158263{col 51}{space 1}   -0.49{col 60}{space 3}0.624{col 68}{space 4}-.2838067{col 81}{space 3} .1702239
{txt}{space 10}road_density_GAP {c |}{col 28}{res}{space 2}-1.826186{col 40}{space 2} 3.408742{col 51}{space 1}   -0.54{col 60}{space 3}0.592{col 68}{space 4}-8.507198{col 81}{space 3} 4.854826
{txt}{space 5}lifeexp_1990_2011_GAP {c |}{col 28}{res}{space 2}  .192456{col 40}{space 2} .1593479{col 51}{space 1}    1.21{col 60}{space 3}0.227{col 68}{space 4}-.1198601{col 81}{space 3}  .504772
{txt}percent_votes1991_1999_GAP {c |}{col 28}{res}{space 2} -.033066{col 40}{space 2} .1406378{col 51}{space 1}   -0.24{col 60}{space 3}0.814{col 68}{space 4} -.308711{col 81}{space 3}  .242579
{txt}{space 14}hilli_region {c |}{col 28}{res}{space 2} .8475976{col 40}{space 2} 1.924634{col 51}{space 1}    0.44{col 60}{space 3}0.660{col 68}{space 4}-2.924616{col 81}{space 3} 4.619811
{txt}{space 11}mountain_region {c |}{col 28}{res}{space 2}-3.266761{col 40}{space 2} 4.442332{col 51}{space 1}   -0.74{col 60}{space 3}0.462{col 68}{space 4}-11.97357{col 81}{space 3} 5.440049
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}-2.595659{col 40}{space 2} 1.213215{col 51}{space 1}   -2.14{col 60}{space 3}0.032{col 68}{space 4}-4.973517{col 81}{space 3}-.2178008
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   sigma_u {c |} {res}         0
                   {txt}sigma_e {c |} {res}  41.34284
                       {txt}rho {c |} {res}         0{txt}   (fraction of variance due to u_i)
{hline 27}{c BT}{hline 64}

{com}. vif, uncen

{txt}    Variable {c |}       VIF       1/VIF  
{hline 13}{c +}{hline 22}
litrate_19~P {c |} {res}     1.66    0.602030
{txt}lifeexp_19~P {c |} {res}     1.58    0.630986
{txt}road_densi~P {c |} {res}     1.43    0.697000
{txt}mountain_r~n {c |} {res}     1.15    0.870161
{txt}percent_vo~P {c |} {res}     1.15    0.873170
{txt}hilli_region {c |} {res}     1.12    0.896766
{txt}{hline 13}{c +}{hline 22}
    Mean VIF {c |} {res}     1.35
{txt}
{com}. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\mjoshi2\Box\2024 Research\NEPAL RESEARCH\Nepal court conflict research\Paper1\Japanese Journal of Political Science\RR1\Clean\RR2\Replication\Nepal Court and Maoist Conflict Onset.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}13 Nov 2025, 11:23:56
{txt}{.-}
{smcl}
{txt}{sf}{ul off}